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Bistaffa, Jesús Cerquides Alessandro Farinelli Filippo; Ramchurn, Sarvapali D.
Algorithms for Graph-Constrained Coalition Formation in the Real World Journal Article
In: ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 4, 0000.
Links | BibTeX | Tags: Coalition Formation, Ridesharing
@article{bistaffaetal2017,
title = {Algorithms for Graph-Constrained Coalition Formation in the Real World},
author = {Jesús Cerquides Alessandro Farinelli Filippo Bistaffa and Sarvapali D. Ramchurn},
doi = {http://dx.doi.org/10.1145/3040967},
journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
volume = {8},
number = {4},
keywords = {Coalition Formation, Ridesharing},
pubstate = {published},
tppubtype = {article}
}
On the distinctiveness of the electricity load profile Journal Article
In: Pattern Recognitio, 0000.
BibTeX | Tags:
@article{BICEGO2018317bb,
title = {On the distinctiveness of the electricity load profile},
journal = {Pattern Recognitio},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
81.
Balsamo, Domenico; Merrett, Geoff V.; Zaghari, Bahareh; Wei, Yang; Ramchurn, Sarvapali; Stein, Sebastian; Weddell, Alexander; Beeby, Stephen
Wearable and autonomous computing for future smart cities: open challenges Proceedings Article
In: 25th International Conference on Software, Telecommunications and Computer Networks, 2017.
@inproceedings{soton414077b,
title = {Wearable and autonomous computing for future smart cities: open challenges},
author = {Domenico Balsamo and Geoff V. Merrett and Bahareh Zaghari and Yang Wei and Sarvapali Ramchurn and Sebastian Stein and Alexander Weddell and Stephen Beeby},
url = {https://eprints.soton.ac.uk/414077/},
year = {2017},
date = {2017-09-01},
booktitle = {25th International Conference on Software, Telecommunications and Computer Networks},
abstract = {The promise of smart cities offers the potential to change the way we live, and refers to the integration of IoT systems for people-centred applications, together with the collection and processing of data, and associated decision making. Central to the realization of this are wearable and autonomous computing systems. There are considerable challenges that exist in this space that require research across different areas of electronics and computer science; it is this multidisciplinary consideration that is novel to this paper. We consider these challenges from different perspectives, involving research in devices, infrastructure and software. Specifically, the challenges considered are related to IoT systems and networking, autonomous computing, wearable sensors and electronics, and the coordination of collectives comprising human and software agents.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The promise of smart cities offers the potential to change the way we live, and refers to the integration of IoT systems for people-centred applications, together with the collection and processing of data, and associated decision making. Central to the realization of this are wearable and autonomous computing systems. There are considerable challenges that exist in this space that require research across different areas of electronics and computer science; it is this multidisciplinary consideration that is novel to this paper. We consider these challenges from different perspectives, involving research in devices, infrastructure and software. Specifically, the challenges considered are related to IoT systems and networking, autonomous computing, wearable sensors and electronics, and the coordination of collectives comprising human and software agents.
82.
Diago, Ndeye Arame; Aknine, Samir; Ramchurn, Sarvapali; Shehory, Onn; Sene, Mbaye
Distributed negotiation for collective decision-making Proceedings Article
In: Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017, pp. 913–920, IEEE Computer Society Press, 2017.
@inproceedings{soton421970,
title = {Distributed negotiation for collective decision-making},
author = {Ndeye Arame Diago and Samir Aknine and Sarvapali Ramchurn and Onn Shehory and Mbaye Sene},
url = {https://eprints.soton.ac.uk/421970/},
year = {2017},
date = {2017-06-01},
booktitle = {Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017},
volume = {2017-November},
pages = {913–920},
publisher = {IEEE Computer Society Press},
abstract = {ensuremath<pensuremath>Collective decision-making is a process in which participants make a collective choice from several alternatives. In this paper, we focus on collective decision contexts in which more than two selfish agents negotiate over multiple issues. We specifically consider a case of joint household energy purchase where the concerned households have to define a collective energy contract. The households involved may each be interested only in a subset of the issues at stake. We devise an effective protocol to regulate the interactions among the (household) agents and reduce their reasoning complexity. The mechanism we introduce is fully decentralized, it facilitates multi-lateral negotiation, and it reduces the complexity of the solution despite the inherent complexity of the problem.ensuremath</pensuremath>},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
ensuremath<pensuremath>Collective decision-making is a process in which participants make a collective choice from several alternatives. In this paper, we focus on collective decision contexts in which more than two selfish agents negotiate over multiple issues. We specifically consider a case of joint household energy purchase where the concerned households have to define a collective energy contract. The households involved may each be interested only in a subset of the issues at stake. We devise an effective protocol to regulate the interactions among the (household) agents and reduce their reasoning complexity. The mechanism we introduce is fully decentralized, it facilitates multi-lateral negotiation, and it reduces the complexity of the solution despite the inherent complexity of the problem.ensuremath</pensuremath>
83.
Shann, Sven Seuken Alper Alan Mike; Ramchurn, Sarvapali
Save Money or Feel Cozy? A Field Experiment Evaluation of a Smart Thermostat that Learns Heating Preferences Proceedings Article
In: Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems, 2017.
@inproceedings{seuken:etal:2017,
title = {Save Money or Feel Cozy? A Field Experiment Evaluation of a Smart Thermostat that Learns Heating Preferences},
author = {Sven Seuken Alper Alan Mike Shann and Sarvapali Ramchurn},
year = {2017},
date = {2017-05-02},
booktitle = {Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
84.
Fischer, Joel E; Greenhalgh, Chris; Jiang, Wenchao; Ramchurn, Sarvapali D; Wu, Feng; Rodden, Tom
In-the-loop or on-the-loop? Interactional arrangements to support team coordination with a planning agent Journal Article
In: Concurrency and Computation: Practice and Experience, vol. 0, no. 0, 2017, (e4082 cpe.4082).
@article{doi:10.1002/cpe.4082,
title = {In-the-loop or on-the-loop? Interactional arrangements to support team coordination with a planning agent},
author = {Joel E Fischer and Chris Greenhalgh and Wenchao Jiang and Sarvapali D Ramchurn and Feng Wu and Tom Rodden},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4082},
doi = {10.1002/cpe.4082},
year = {2017},
date = {2017-03-06},
journal = {Concurrency and Computation: Practice and Experience},
volume = {0},
number = {0},
abstract = {Summary In this paper, we present the study of interactional arrangements that support the collaboration of headquarters (HQ), field responders, and a computational planning agent in a time-critical task setting created by a mixed-reality game. Interactional arrangements define the extent to which control is distributed between the collaborative parties. We provide 2 field trials, one to study an “on-the-loop” arrangement in which HQ monitors and intervenes in agent instructions to field players on demand and the other, to study a version that places HQ more tightly “in-the-loop.” The studies provide an understanding of the sociotechnical collaboration between players and the agent in these interactional arrangements by conducting interaction analysis of video recordings and game log data. The first field trial focuses on the collaboration of field responders with the planning agent. Findings highlight how players negotiate the agent guidance within the social interaction of the collocated teams. The second field trial focuses on the collaboration between the automated planning agent and the HQ. We find that the human coordinator and the agent can successfully work together in most cases, with human coordinators inspecting and “correcting” the agent-proposed plans. Through this field trial-driven development process, we generalise interaction design implications of automated planning agents around the themes of supporting common ground and mixed-initiative planning.},
note = {e4082 cpe.4082},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Summary In this paper, we present the study of interactional arrangements that support the collaboration of headquarters (HQ), field responders, and a computational planning agent in a time-critical task setting created by a mixed-reality game. Interactional arrangements define the extent to which control is distributed between the collaborative parties. We provide 2 field trials, one to study an “on-the-loop” arrangement in which HQ monitors and intervenes in agent instructions to field players on demand and the other, to study a version that places HQ more tightly “in-the-loop.” The studies provide an understanding of the sociotechnical collaboration between players and the agent in these interactional arrangements by conducting interaction analysis of video recordings and game log data. The first field trial focuses on the collaboration of field responders with the planning agent. Findings highlight how players negotiate the agent guidance within the social interaction of the collocated teams. The second field trial focuses on the collaboration between the automated planning agent and the HQ. We find that the human coordinator and the agent can successfully work together in most cases, with human coordinators inspecting and “correcting” the agent-proposed plans. Through this field trial-driven development process, we generalise interaction design implications of automated planning agents around the themes of supporting common ground and mixed-initiative planning.
85.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali
Multimodal human aerobotic interaction Book Section
In: Issa, Tomayess; Kommers, Piet; Issa, Theodora; Isa'ias, Pedro; Issa, Touma B. (Ed.): Smart Technology Applications in Business Environments, pp. 39–62, IGI Global, 2017.
@incollection{soton406888b,
title = {Multimodal human aerobotic interaction},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali Ramchurn},
editor = {Tomayess Issa and Piet Kommers and Theodora Issa and Pedro Isa'ias and Touma B. Issa},
url = {https://eprints.soton.ac.uk/406888/},
year = {2017},
date = {2017-03-01},
booktitle = {Smart Technology Applications in Business Environments},
pages = {39–62},
publisher = {IGI Global},
abstract = {This chapter discusses HCI interfaces used in controlling aerial robotic systems (otherwise known as aerobots). The autonomy control level of aerobot is also discussed. However, due to the limitations of existing models, a novel classification model of autonomy, specifically designed for multirotor aerial robots, called the navigation control autonomy (nCA) model is also developed. Unlike the existing models such as the AFRL and ONR, this model is presented in tiers and has a two-dimensional pyramidal structure. This model is able to identify the control void existing beyond tier-one autonomy components modes and to map the upper and lower limits of control interfaces. Two solutions are suggested for dealing with the existing control void and the limitations of the RC joystick controller ? the multimodal HHI-like interface and the unimodal BCI interface. In addition to these, some human factors based performance measurement is recommended, and the plans for further works presented.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
This chapter discusses HCI interfaces used in controlling aerial robotic systems (otherwise known as aerobots). The autonomy control level of aerobot is also discussed. However, due to the limitations of existing models, a novel classification model of autonomy, specifically designed for multirotor aerial robots, called the navigation control autonomy (nCA) model is also developed. Unlike the existing models such as the AFRL and ONR, this model is presented in tiers and has a two-dimensional pyramidal structure. This model is able to identify the control void existing beyond tier-one autonomy components modes and to map the upper and lower limits of control interfaces. Two solutions are suggested for dealing with the existing control void and the limitations of the RC joystick controller ? the multimodal HHI-like interface and the unimodal BCI interface. In addition to these, some human factors based performance measurement is recommended, and the plans for further works presented.
86.
Bistaffa, Jesús Cerquides Alessandro Farinelli Filippo; Ramchurn, Sarvapali D.
Algorithms for Graph-Constrained Coalition Formation in the Real World Journal Article
In: ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 4, 2017.
@article{bistaffaetal2017b,
title = {Algorithms for Graph-Constrained Coalition Formation in the Real World},
author = {Jesús Cerquides Alessandro Farinelli Filippo Bistaffa and Sarvapali D. Ramchurn},
url = {http://www.sramchurn.com/wp-content/uploads/2017/03/2017tist.pdf},
doi = {http://dx.doi.org/10.1145/3040967},
year = {2017},
date = {2017-02-11},
journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
volume = {8},
number = {4},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
87.
Chalkiadakis, Sarvapali Alessandro Farinelli; Ramchurn Filippo Bistaffa Georgios
A Cooperative Game-Theoretic Approach to the Social Ridesharing Problem Journal Article
In: Artificial Intelligence Journal, pp. (accepted), 2017.
@article{bistaffa:etal:2017b,
title = {A Cooperative Game-Theoretic Approach to the Social Ridesharing Problem},
author = {Sarvapali Alessandro Farinelli; Ramchurn Filippo Bistaffa Georgios Chalkiadakis},
url = {http://www.sciencedirect.com/science/article/pii/S0004370217300243},
year = {2017},
date = {2017-02-11},
journal = {Artificial Intelligence Journal},
pages = {(accepted)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
88.
Farinelli, Alessandro; Bicego, Manuele; Bistaffa, Filippo; Ramchurn, Sarvapali D.
A Hierarchical Clustering Approach to Large-scale Near-optimal Coalition Formation with Quality Guarantees Journal Article
In: Engineering Applications of Artificial Intelligence (EAAI), vol. 57, pp. 170-185, 2017.
@article{farinelli:etal:2017,
title = {A Hierarchical Clustering Approach to Large-scale Near-optimal Coalition Formation with Quality Guarantees},
author = {Alessandro Farinelli and Manuele Bicego and Filippo Bistaffa and Sarvapali D. Ramchurn},
url = {http://www.sramchurn.com/wp-content/uploads/2017/02/1-s2.0-S0952197616302536-main.pdf},
doi = {http://dx.doi.org/10.1016/j.engappai.2016.12.018},
year = {2017},
date = {2017-02-01},
journal = {Engineering Applications of Artificial Intelligence (EAAI)},
volume = {57},
pages = {170-185},
abstract = {Coalition formation is a fundamental approach to multi-agent coordination, and a key challenge in this context
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Coalition formation is a fundamental approach to multi-agent coordination, and a key challenge in this context
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.
89.
Cruz, Francisco; Espinosa, Antonio; Moure, Juan C.; Cerquides, Jesus; Rodriguez-Aguilar, Juan A.; Svensson, Kim; Ramchurn, Sarvapali D.
Coalition structure generation problems: optimization and parallelization of the IDP algorithm in multicore systems Journal Article
In: Concurrency and Computation: Practice and Experience, vol. 29, no. 5, pp. e3969–n/a, 2017, ISSN: 1532-0634, (e3969 cpe.3969).
@article{CPE:CPE3969,
title = {Coalition structure generation problems: optimization and parallelization of the IDP algorithm in multicore systems},
author = {Francisco Cruz and Antonio Espinosa and Juan C. Moure and Jesus Cerquides and Juan A. Rodriguez-Aguilar and Kim Svensson and Sarvapali D. Ramchurn},
url = {http://dx.doi.org/10.1002/cpe.3969},
doi = {10.1002/cpe.3969},
issn = {1532-0634},
year = {2017},
date = {2017-01-01},
journal = {Concurrency and Computation: Practice and Experience},
volume = {29},
number = {5},
pages = {e3969–n/a},
publisher = {John Wiley & Sons, Ltd},
note = {e3969 cpe.3969},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
90.
Ramchurn, Sarvapali; Simpson, Edwin; Fischer, Joel; Huynh, Trung Dong; Ikuno, Yuki; Reece, Steven; Jiang, Wenchao; Wu, Feng; Flann, Jack; Roberts, S. J.; Moreau, Luc; Rodden, T.; Jennings, N. R.
A Disaster Response System based on Human-Agent Collectives Journal Article
In: Journal of Artificial Intelligence Research, vol. 57, pp. 661-708, 2016.
@article{eps374070b,
title = {A Disaster Response System based on Human-Agent Collectives},
author = {Sarvapali Ramchurn and Edwin Simpson and Joel Fischer and Trung Dong Huynh and Yuki Ikuno and Steven Reece and Wenchao Jiang and Feng Wu and Jack Flann and S. J. Roberts and Luc Moreau and T. Rodden and N. R. Jennings},
url = {http://www.jair.org/media/5098/live-5098-9699-jair.pdf},
year = {2016},
date = {2016-12-01},
journal = {Journal of Artificial Intelligence Research},
volume = {57},
pages = {661-708},
abstract = {Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks pose significant challenges for emergency responders. First, they have to develop an understanding of the unfolding event either using their own resources or through third-parties such as the local population and agencies. Second, based on the information gathered, they need to deploy their teams in a flexible manner, ensuring that each team performs tasks in The most effective way. Third, given the dynamic nature of a disaster space, and the uncertainties involved in performing rescue missions, information about the disaster space and the actors within it needs to be managed to ensure that responders are always acting on up-to-date and trusted information. Against this background, this paper proposes a novel disaster response system called HAC-ER. Thus HAC-ER interweaves humans and agents, both robotic and software, in social relationships that augment their individual and collective capabilities. To design HAC-ER, we involved end-users including both experts and volunteers in a several participatory design workshops, lab studies, and field trials of increasingly advanced prototypes of individual components of HAC-ER as well as the overall system. This process generated a number of new quantitative and qualitative results but also raised a number of new research questions. HAC-ER thus demonstrates how such Human-Agent Collectives (HACs) can address key challenges in disaster response. Specifically, we show how HAC-ER utilises crowdsourcing combined with machine learning to obtain most important situational awareness from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments, as well as task planning for responders on the ground. Finally, HAC-ER incorporates an infrastructure and the associated intelligence for tracking and utilising the provenance of information shared across the entire system to ensure its accountability. We individually validate each of these elements of HAC-ER and show how they perform against standard (non-HAC) baselines and also elaborate on the evaluation of the overall system.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks pose significant challenges for emergency responders. First, they have to develop an understanding of the unfolding event either using their own resources or through third-parties such as the local population and agencies. Second, based on the information gathered, they need to deploy their teams in a flexible manner, ensuring that each team performs tasks in The most effective way. Third, given the dynamic nature of a disaster space, and the uncertainties involved in performing rescue missions, information about the disaster space and the actors within it needs to be managed to ensure that responders are always acting on up-to-date and trusted information. Against this background, this paper proposes a novel disaster response system called HAC-ER. Thus HAC-ER interweaves humans and agents, both robotic and software, in social relationships that augment their individual and collective capabilities. To design HAC-ER, we involved end-users including both experts and volunteers in a several participatory design workshops, lab studies, and field trials of increasingly advanced prototypes of individual components of HAC-ER as well as the overall system. This process generated a number of new quantitative and qualitative results but also raised a number of new research questions. HAC-ER thus demonstrates how such Human-Agent Collectives (HACs) can address key challenges in disaster response. Specifically, we show how HAC-ER utilises crowdsourcing combined with machine learning to obtain most important situational awareness from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments, as well as task planning for responders on the ground. Finally, HAC-ER incorporates an infrastructure and the associated intelligence for tracking and utilising the provenance of information shared across the entire system to ensure its accountability. We individually validate each of these elements of HAC-ER and show how they perform against standard (non-HAC) baselines and also elaborate on the evaluation of the overall system.
91.
Garcia, Pedro Garcia; Costanza, Enrico; Verame, Jhim; Ramchurn, Sarvapali D.
The potential of physical motion cues: changing people?s perception of robots? performance Proceedings Article
In: UbiComp 2016: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM, 2016.
@inproceedings{eps398009,
title = {The potential of physical motion cues: changing people?s perception of robots? performance},
author = {Pedro Garcia Garcia and Enrico Costanza and Jhim Verame and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/398009/},
year = {2016},
date = {2016-09-01},
booktitle = {UbiComp 2016: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing},
publisher = {ACM},
abstract = {Autonomous robotic systems can automatically perform actions on behalf of users in the domestic environment to help people in their daily activities. Such systems aim to reduce users' cognitive and physical workload, and improve wellbeing. While the benefits of these systems are clear, recent studies suggest that users may misconstrue their performance of tasks. We see an opportunity in designing interaction techniques that improve how users perceive the performance of such systems. We report two lab studies (N=16 each) designed to investigate whether showing physical motion, which is showing the process of a system through movement (that is intrinsic to the system's task), of an autonomous system as it completes its task, affects how users perceive its performance. To ensure our studies are ecologically valid and to motivate participants to provide thoughtful responses we adopted consensus-oriented financial incentives. Our results suggest that physical presence does yield higher performance ratings.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Autonomous robotic systems can automatically perform actions on behalf of users in the domestic environment to help people in their daily activities. Such systems aim to reduce users' cognitive and physical workload, and improve wellbeing. While the benefits of these systems are clear, recent studies suggest that users may misconstrue their performance of tasks. We see an opportunity in designing interaction techniques that improve how users perceive the performance of such systems. We report two lab studies (N=16 each) designed to investigate whether showing physical motion, which is showing the process of a system through movement (that is intrinsic to the system's task), of an autonomous system as it completes its task, affects how users perceive its performance. To ensure our studies are ecologically valid and to motivate participants to provide thoughtful responses we adopted consensus-oriented financial incentives. Our results suggest that physical presence does yield higher performance ratings.
92.
Truong, Ngoc Cuong; Baarslag, Tim; Ramchurn, Sarvapali D.; Tran-Thanh, Long
Interactive scheduling of appliance usage in the home Proceedings Article
In: 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 869–875, 2016.
@inproceedings{eps396670,
title = {Interactive scheduling of appliance usage in the home},
author = {Ngoc Cuong Truong and Tim Baarslag and Sarvapali D. Ramchurn and Long Tran-Thanh},
url = {http://eprints.soton.ac.uk/396670/},
year = {2016},
date = {2016-07-12},
booktitle = {25th International Joint Conference on Artificial Intelligence (IJCAI-16)},
pages = {869–875},
abstract = {We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user?s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real?world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user?s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real?world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks
93.
Baker, Chris; Ramchurn, Sarvapali D.; Teacy, Luke; Jennings, Nicholas
Planning search and rescue missions for UAV teams Proceedings Article
In: PAIS 2016: Conference on Prestigious Applications of Intelligent Systems at ECAI 2016, 2016.
@inproceedings{eps396996,
title = {Planning search and rescue missions for UAV teams},
author = {Chris Baker and Sarvapali D. Ramchurn and Luke Teacy and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/396996/},
year = {2016},
date = {2016-06-01},
booktitle = {PAIS 2016: Conference on Prestigious Applications of Intelligent Systems at ECAI 2016},
abstract = {The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out aerial surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. To aid in this process, it is desirable to exploit the increasing availability of data about a disaster from sources such as crowd reports, satellite re- mote sensing, or manned reconnaissance. In particular, such information can be a valuable resource to drive the planning of UAV flight paths over a space in order to discover people who are in danger. However challenges of computational tractability remain when planning over the very large action spaces that result. To overcome these, we introduce the survivor discovery problem and present as our solution, the first example of a continuous factored coordinated Monte Carlo tree search algorithm. Our evaluation against state of the art benchmarks show that our algorithm, Co-CMCTS, is able to localise more casualties faster than standard approaches by 7% or more on simulations with real-world data.},
keywords = {},
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The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out aerial surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. To aid in this process, it is desirable to exploit the increasing availability of data about a disaster from sources such as crowd reports, satellite re- mote sensing, or manned reconnaissance. In particular, such information can be a valuable resource to drive the planning of UAV flight paths over a space in order to discover people who are in danger. However challenges of computational tractability remain when planning over the very large action spaces that result. To overcome these, we introduce the survivor discovery problem and present as our solution, the first example of a continuous factored coordinated Monte Carlo tree search algorithm. Our evaluation against state of the art benchmarks show that our algorithm, Co-CMCTS, is able to localise more casualties faster than standard approaches by 7% or more on simulations with real-world data.
94.
Fisher, Joel; Crabtree, Andy; Rodden, Tom; Colley, James; Costanza, Enrico; Jewell, Michael; Ramchurn, Sarvapali
"Just whack it on until it gets hot, then turn it off": Working with IoT Data in the Home Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385056,
title = {"Just whack it on until it gets hot, then turn it off": Working with IoT Data in the Home},
author = {Joel Fisher and Andy Crabtree and Tom Rodden and James Colley and Enrico Costanza and Michael Jewell and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/385056/},
year = {2016},
date = {2016-05-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
keywords = {},
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95.
Zhao, Dengji; Ramchurn, Sarvapali D.; Jennings, Nicholas
Fault tolerant mechanism design for general task allocation Proceedings Article
In: The 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), International Foundation for Autonomous Agents and Multiagent Systems, 2016.
@inproceedings{eps388365,
title = {Fault tolerant mechanism design for general task allocation},
author = {Dengji Zhao and Sarvapali D. Ramchurn and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/388365/},
year = {2016},
date = {2016-05-01},
booktitle = {The 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016)},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
abstract = {We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an allocation that maximises social welfare while taking their execution uncertainty into account (i.e., fault tolerant). To achieve this, we show that the post-execution verification (PEV)-based mechanism presented by Porter et al. (2008) is applicable if and only if agents' valuations are risk-neutral (i.e., the solution is almost universal). We then consider a more advanced setting where an agent's execution uncertainty is not completely predictable by the agent alone but aggregated from all agents' private opinions (known as trust). We show that PEV-based mechanism with trust is still applicable if and only if the trust aggregation is multilinear. Given this characterisation, we further demonstrate how this mechanism can be successfully applied in a real-world setting. Finally, we draw the parallels between our results and the literature of efficient mechanism design with general interdependent valuations.},
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We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an allocation that maximises social welfare while taking their execution uncertainty into account (i.e., fault tolerant). To achieve this, we show that the post-execution verification (PEV)-based mechanism presented by Porter et al. (2008) is applicable if and only if agents' valuations are risk-neutral (i.e., the solution is almost universal). We then consider a more advanced setting where an agent's execution uncertainty is not completely predictable by the agent alone but aggregated from all agents' private opinions (known as trust). We show that PEV-based mechanism with trust is still applicable if and only if the trust aggregation is multilinear. Given this characterisation, we further demonstrate how this mechanism can be successfully applied in a real-world setting. Finally, we draw the parallels between our results and the literature of efficient mechanism design with general interdependent valuations.
96.
Wu, Feng; Ramchurn, Sarvapali D.; Chen, Xiaoping
Coordinating human-UAV teams in disaster response Proceedings Article
In: International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 524–530, 2016.
@inproceedings{eps393725,
title = {Coordinating human-UAV teams in disaster response},
author = {Feng Wu and Sarvapali D. Ramchurn and Xiaoping Chen},
url = {http://eprints.soton.ac.uk/393725/},
year = {2016},
date = {2016-04-01},
booktitle = {International Joint Conference on Artificial Intelligence (IJCAI-16)},
pages = {524–530},
abstract = {We consider a disaster response scenario where emergency responders have to complete rescue tasks in dynamic and uncertain environment with the assistance of multiple UAVs to collect information about the disaster space. To capture the uncertainty and partial observability of the domain, we model this problem as a POMDP. However, the resulting model is computationally intractable and cannot be solved by most existing POMDP solvers due to the large state and action spaces. By exploiting the problem structure we propose a novel online planning algorithm to solve this model. Specifically, we generate plans for the responders based on Monte-Carlo simulations and compute actions for the UAVs according to the value of information. Our empirical results confirm that our algorithm significantly outperforms the state-of-the-art both in time and solution quality.},
keywords = {},
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We consider a disaster response scenario where emergency responders have to complete rescue tasks in dynamic and uncertain environment with the assistance of multiple UAVs to collect information about the disaster space. To capture the uncertainty and partial observability of the domain, we model this problem as a POMDP. However, the resulting model is computationally intractable and cannot be solved by most existing POMDP solvers due to the large state and action spaces. By exploiting the problem structure we propose a novel online planning algorithm to solve this model. Specifically, we generate plans for the responders based on Monte-Carlo simulations and compute actions for the UAVs according to the value of information. Our empirical results confirm that our algorithm significantly outperforms the state-of-the-art both in time and solution quality.
97.
Baker, Chris; Ramchurn, Gopal; Teacy, Luke; Jennings, Nicholas
Factored Monte-Carlo tree search for coordinating UAVs in disaster response Proceedings Article
In: Distributed and Multi-Agent Planning, ICAPS, 2016.
@inproceedings{eps393649,
title = {Factored Monte-Carlo tree search for coordinating UAVs in disaster response},
author = {Chris Baker and Gopal Ramchurn and Luke Teacy and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/393649/},
year = {2016},
date = {2016-04-01},
booktitle = {Distributed and Multi-Agent Planning},
publisher = {ICAPS},
abstract = {The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. However, an increase in the availability of real-time data about a disaster from sources such as crowd reports or satellites presents a valuable source of information to drive the planning of UAV flight paths over a space in order to discover people who are in danger. Nevertheless challenges remain when planning over the very large action spaces that result. To this end, we introduce the survivor discovery problem and present as our solution, the first example of a factored coordinated Monte Carlo tree search algorithm to perform decentralised path planning for multiple coordinated UAVs. Our evaluation against standard benchmarks show that our algorithm, Co-MCTS, is able to find more casualties faster than standard approaches by 10% or more on simulations with real-world data from the 2010 Haiti earthquake.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. However, an increase in the availability of real-time data about a disaster from sources such as crowd reports or satellites presents a valuable source of information to drive the planning of UAV flight paths over a space in order to discover people who are in danger. Nevertheless challenges remain when planning over the very large action spaces that result. To this end, we introduce the survivor discovery problem and present as our solution, the first example of a factored coordinated Monte Carlo tree search algorithm to perform decentralised path planning for multiple coordinated UAVs. Our evaluation against standard benchmarks show that our algorithm, Co-MCTS, is able to find more casualties faster than standard approaches by 10% or more on simulations with real-world data from the 2010 Haiti earthquake.
98.
Verame, Jhim Kiel M.; Costanza, Enrico; Ramchurn, Sarvapali
The Effect of Displaying System Confidence Information on the Usage of Autonomous Systems for Non-specialist Applications: A Lab Study Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385069b,
title = {The Effect of Displaying System Confidence Information on the Usage of Autonomous Systems for Non-specialist Applications: A Lab Study},
author = {Jhim Kiel M. Verame and Enrico Costanza and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/385069/},
year = {2016},
date = {2016-01-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
abstract = {Autonomous systems are designed to take actions on behalf of users, acting autonomously upon data from sensors or online sources. As such, the design of interaction mechanisms that enable users to understand the operation of autonomous systems and flexibly delegate or regain control is an open challenge for HCI. Against this background, in this paper we report on a lab study designed to investigate whether displaying the confidence of an autonomous system about the quality of its work, which we call its confidence information, can improve user acceptance and interaction with autonomous systems. The results demonstrate that confidence information encourages the usage of the autonomous system we tested, compared to a situation where such information is not available. Furthermore, an additional contribution of our work is the methodology we employ to study users' incentives to do work in collaboration with the autonomous system. In experiments comparing different incentive strategies, our results indicate that our translation of behavioural economics research methods to HCI can support the study of interactions with autonomous systems in the lab.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Autonomous systems are designed to take actions on behalf of users, acting autonomously upon data from sensors or online sources. As such, the design of interaction mechanisms that enable users to understand the operation of autonomous systems and flexibly delegate or regain control is an open challenge for HCI. Against this background, in this paper we report on a lab study designed to investigate whether displaying the confidence of an autonomous system about the quality of its work, which we call its confidence information, can improve user acceptance and interaction with autonomous systems. The results demonstrate that confidence information encourages the usage of the autonomous system we tested, compared to a situation where such information is not available. Furthermore, an additional contribution of our work is the methodology we employ to study users' incentives to do work in collaboration with the autonomous system. In experiments comparing different incentive strategies, our results indicate that our translation of behavioural economics research methods to HCI can support the study of interactions with autonomous systems in the lab.
99.
Alan, Alper Turan; Shann, Mike; Costanza, Enrico; Ramchurn, Sarvapali; Seuken, Sven
It is too hot: an in-situ study of three designs for heating Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385045b,
title = {It is too hot: an in-situ study of three designs for heating},
author = {Alper Turan Alan and Mike Shann and Enrico Costanza and Sarvapali Ramchurn and Sven Seuken},
url = {http://eprints.soton.ac.uk/385045/},
year = {2016},
date = {2016-01-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
abstract = {Smart technologies are becoming increasingly ubiquitous, and consequently transforming our lives. Domestic energy use is one of the most talked domain that people may greatly benefit from these technologies. Given this, it is important to understand interactions with smart systems within people?s everyday lives. To this end, we developed and deployed the first heating system that allows its users to control their home heating with real-time prices. In particular, we implemented three different designs of our heating system, and evaluated them with 30 UK households in a four-week in the wild study. Our findings through thematic analysis show that our participants formed different understandings and expectations of the system, and used it in various ways to effectively respond to real-time prices while maintaining their thermal comfort. These findings contribute to our understanding of interactions with smart energy systems and provide key design implications for developing them.},
keywords = {},
pubstate = {published},
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}
Smart technologies are becoming increasingly ubiquitous, and consequently transforming our lives. Domestic energy use is one of the most talked domain that people may greatly benefit from these technologies. Given this, it is important to understand interactions with smart systems within people?s everyday lives. To this end, we developed and deployed the first heating system that allows its users to control their home heating with real-time prices. In particular, we implemented three different designs of our heating system, and evaluated them with 30 UK households in a four-week in the wild study. Our findings through thematic analysis show that our participants formed different understandings and expectations of the system, and used it in various ways to effectively respond to real-time prices while maintaining their thermal comfort. These findings contribute to our understanding of interactions with smart energy systems and provide key design implications for developing them.
100.
Bandhyopadhyay, Sambaran; Narayanam, Ramasuri; Kumar, Pratyush; Ramchurn, Sarvapali Dyanand; Arya, Vijay
An Axiomatic Framework for Ex-Ante Dynamic Pricing Mechanisms in Smart Grid Proceedings Article
In: Proceedings of 30th AAAI Conference on Artificial Intelligence (AAAI), AAAI Press, 2016.
@inproceedings{eps386417,
title = {An Axiomatic Framework for Ex-Ante Dynamic Pricing Mechanisms in Smart Grid},
author = {Sambaran Bandhyopadhyay and Ramasuri Narayanam and Pratyush Kumar and Sarvapali Dyanand Ramchurn and Vijay Arya},
url = {http://eprints.soton.ac.uk/386417/},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of 30th AAAI Conference on Artificial Intelligence (AAAI)},
publisher = {AAAI Press},
abstract = {In electricity markets, the choice of the right pricing regime is crucial for the utilities because the price they charge to their consumers, in anticipation of their demand in real-time, is a key determinant of their profits and ultimately their survival in competitive energy markets. Among the existing pricing regimes, in this paper, we consider ex-ante dynamic pricing schemes as (i) they help to address the peak demand problem (a crucial problem in smart grids), and (ii) they are transparent and fair to consumers as the cost of electricity can be calculated before the actual consumption. In particular, we propose an axiomatic framework that establishes the conceptual underpinnings of the class of ex-ante dynamic pricing schemes.We first propose five key axioms that reflect the criteria that are vital for energy utilities and their relationship with consumers. We then prove an impossibility theorem to show that there is no pricing regime that satisfies all the five axioms simultaneously.We also study multiple cost functions arising from various pricing regimes to examine the subset of axioms that they satisfy. We believe that our proposed framework in this paper is first of its kind to evaluate the class of ex-ante dynamic pricing schemes in a manner that can be operationalised by energy utilities.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In electricity markets, the choice of the right pricing regime is crucial for the utilities because the price they charge to their consumers, in anticipation of their demand in real-time, is a key determinant of their profits and ultimately their survival in competitive energy markets. Among the existing pricing regimes, in this paper, we consider ex-ante dynamic pricing schemes as (i) they help to address the peak demand problem (a crucial problem in smart grids), and (ii) they are transparent and fair to consumers as the cost of electricity can be calculated before the actual consumption. In particular, we propose an axiomatic framework that establishes the conceptual underpinnings of the class of ex-ante dynamic pricing schemes.We first propose five key axioms that reflect the criteria that are vital for energy utilities and their relationship with consumers. We then prove an impossibility theorem to show that there is no pricing regime that satisfies all the five axioms simultaneously.We also study multiple cost functions arising from various pricing regimes to examine the subset of axioms that they satisfy. We believe that our proposed framework in this paper is first of its kind to evaluate the class of ex-ante dynamic pricing schemes in a manner that can be operationalised by energy utilities.
0000
Bistaffa, Jesús Cerquides Alessandro Farinelli Filippo; Ramchurn, Sarvapali D.
Algorithms for Graph-Constrained Coalition Formation in the Real World Journal Article
In: ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 4, 0000.
Links | BibTeX | Tags: Coalition Formation, Ridesharing
@article{bistaffaetal2017,
title = {Algorithms for Graph-Constrained Coalition Formation in the Real World},
author = {Jesús Cerquides Alessandro Farinelli Filippo Bistaffa and Sarvapali D. Ramchurn},
doi = {http://dx.doi.org/10.1145/3040967},
journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
volume = {8},
number = {4},
keywords = {Coalition Formation, Ridesharing},
pubstate = {published},
tppubtype = {article}
}
On the distinctiveness of the electricity load profile Journal Article
In: Pattern Recognitio, 0000.
BibTeX | Tags:
@article{BICEGO2018317bb,
title = {On the distinctiveness of the electricity load profile},
journal = {Pattern Recognitio},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
81.
Balsamo, Domenico; Merrett, Geoff V.; Zaghari, Bahareh; Wei, Yang; Ramchurn, Sarvapali; Stein, Sebastian; Weddell, Alexander; Beeby, Stephen
Wearable and autonomous computing for future smart cities: open challenges Proceedings Article
In: 25th International Conference on Software, Telecommunications and Computer Networks, 2017.
@inproceedings{soton414077b,
title = {Wearable and autonomous computing for future smart cities: open challenges},
author = {Domenico Balsamo and Geoff V. Merrett and Bahareh Zaghari and Yang Wei and Sarvapali Ramchurn and Sebastian Stein and Alexander Weddell and Stephen Beeby},
url = {https://eprints.soton.ac.uk/414077/},
year = {2017},
date = {2017-09-01},
booktitle = {25th International Conference on Software, Telecommunications and Computer Networks},
abstract = {The promise of smart cities offers the potential to change the way we live, and refers to the integration of IoT systems for people-centred applications, together with the collection and processing of data, and associated decision making. Central to the realization of this are wearable and autonomous computing systems. There are considerable challenges that exist in this space that require research across different areas of electronics and computer science; it is this multidisciplinary consideration that is novel to this paper. We consider these challenges from different perspectives, involving research in devices, infrastructure and software. Specifically, the challenges considered are related to IoT systems and networking, autonomous computing, wearable sensors and electronics, and the coordination of collectives comprising human and software agents.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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The promise of smart cities offers the potential to change the way we live, and refers to the integration of IoT systems for people-centred applications, together with the collection and processing of data, and associated decision making. Central to the realization of this are wearable and autonomous computing systems. There are considerable challenges that exist in this space that require research across different areas of electronics and computer science; it is this multidisciplinary consideration that is novel to this paper. We consider these challenges from different perspectives, involving research in devices, infrastructure and software. Specifically, the challenges considered are related to IoT systems and networking, autonomous computing, wearable sensors and electronics, and the coordination of collectives comprising human and software agents.
82.
Diago, Ndeye Arame; Aknine, Samir; Ramchurn, Sarvapali; Shehory, Onn; Sene, Mbaye
Distributed negotiation for collective decision-making Proceedings Article
In: Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017, pp. 913–920, IEEE Computer Society Press, 2017.
@inproceedings{soton421970,
title = {Distributed negotiation for collective decision-making},
author = {Ndeye Arame Diago and Samir Aknine and Sarvapali Ramchurn and Onn Shehory and Mbaye Sene},
url = {https://eprints.soton.ac.uk/421970/},
year = {2017},
date = {2017-06-01},
booktitle = {Proceedings - 2017 International Conference on Tools with Artificial Intelligence, ICTAI 2017},
volume = {2017-November},
pages = {913–920},
publisher = {IEEE Computer Society Press},
abstract = {ensuremath<pensuremath>Collective decision-making is a process in which participants make a collective choice from several alternatives. In this paper, we focus on collective decision contexts in which more than two selfish agents negotiate over multiple issues. We specifically consider a case of joint household energy purchase where the concerned households have to define a collective energy contract. The households involved may each be interested only in a subset of the issues at stake. We devise an effective protocol to regulate the interactions among the (household) agents and reduce their reasoning complexity. The mechanism we introduce is fully decentralized, it facilitates multi-lateral negotiation, and it reduces the complexity of the solution despite the inherent complexity of the problem.ensuremath</pensuremath>},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
ensuremath<pensuremath>Collective decision-making is a process in which participants make a collective choice from several alternatives. In this paper, we focus on collective decision contexts in which more than two selfish agents negotiate over multiple issues. We specifically consider a case of joint household energy purchase where the concerned households have to define a collective energy contract. The households involved may each be interested only in a subset of the issues at stake. We devise an effective protocol to regulate the interactions among the (household) agents and reduce their reasoning complexity. The mechanism we introduce is fully decentralized, it facilitates multi-lateral negotiation, and it reduces the complexity of the solution despite the inherent complexity of the problem.ensuremath</pensuremath>
83.
Shann, Sven Seuken Alper Alan Mike; Ramchurn, Sarvapali
Save Money or Feel Cozy? A Field Experiment Evaluation of a Smart Thermostat that Learns Heating Preferences Proceedings Article
In: Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems, 2017.
@inproceedings{seuken:etal:2017,
title = {Save Money or Feel Cozy? A Field Experiment Evaluation of a Smart Thermostat that Learns Heating Preferences},
author = {Sven Seuken Alper Alan Mike Shann and Sarvapali Ramchurn},
year = {2017},
date = {2017-05-02},
booktitle = {Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
84.
Fischer, Joel E; Greenhalgh, Chris; Jiang, Wenchao; Ramchurn, Sarvapali D; Wu, Feng; Rodden, Tom
In-the-loop or on-the-loop? Interactional arrangements to support team coordination with a planning agent Journal Article
In: Concurrency and Computation: Practice and Experience, vol. 0, no. 0, 2017, (e4082 cpe.4082).
@article{doi:10.1002/cpe.4082,
title = {In-the-loop or on-the-loop? Interactional arrangements to support team coordination with a planning agent},
author = {Joel E Fischer and Chris Greenhalgh and Wenchao Jiang and Sarvapali D Ramchurn and Feng Wu and Tom Rodden},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4082},
doi = {10.1002/cpe.4082},
year = {2017},
date = {2017-03-06},
journal = {Concurrency and Computation: Practice and Experience},
volume = {0},
number = {0},
abstract = {Summary In this paper, we present the study of interactional arrangements that support the collaboration of headquarters (HQ), field responders, and a computational planning agent in a time-critical task setting created by a mixed-reality game. Interactional arrangements define the extent to which control is distributed between the collaborative parties. We provide 2 field trials, one to study an “on-the-loop” arrangement in which HQ monitors and intervenes in agent instructions to field players on demand and the other, to study a version that places HQ more tightly “in-the-loop.” The studies provide an understanding of the sociotechnical collaboration between players and the agent in these interactional arrangements by conducting interaction analysis of video recordings and game log data. The first field trial focuses on the collaboration of field responders with the planning agent. Findings highlight how players negotiate the agent guidance within the social interaction of the collocated teams. The second field trial focuses on the collaboration between the automated planning agent and the HQ. We find that the human coordinator and the agent can successfully work together in most cases, with human coordinators inspecting and “correcting” the agent-proposed plans. Through this field trial-driven development process, we generalise interaction design implications of automated planning agents around the themes of supporting common ground and mixed-initiative planning.},
note = {e4082 cpe.4082},
keywords = {},
pubstate = {published},
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}
Summary In this paper, we present the study of interactional arrangements that support the collaboration of headquarters (HQ), field responders, and a computational planning agent in a time-critical task setting created by a mixed-reality game. Interactional arrangements define the extent to which control is distributed between the collaborative parties. We provide 2 field trials, one to study an “on-the-loop” arrangement in which HQ monitors and intervenes in agent instructions to field players on demand and the other, to study a version that places HQ more tightly “in-the-loop.” The studies provide an understanding of the sociotechnical collaboration between players and the agent in these interactional arrangements by conducting interaction analysis of video recordings and game log data. The first field trial focuses on the collaboration of field responders with the planning agent. Findings highlight how players negotiate the agent guidance within the social interaction of the collocated teams. The second field trial focuses on the collaboration between the automated planning agent and the HQ. We find that the human coordinator and the agent can successfully work together in most cases, with human coordinators inspecting and “correcting” the agent-proposed plans. Through this field trial-driven development process, we generalise interaction design implications of automated planning agents around the themes of supporting common ground and mixed-initiative planning.
85.
Ayodeji, Opeyemi Abioye; Prior, Stephen; Thomas, Trevor; Saddington, Peter; Ramchurn, Sarvapali
Multimodal human aerobotic interaction Book Section
In: Issa, Tomayess; Kommers, Piet; Issa, Theodora; Isa'ias, Pedro; Issa, Touma B. (Ed.): Smart Technology Applications in Business Environments, pp. 39–62, IGI Global, 2017.
@incollection{soton406888b,
title = {Multimodal human aerobotic interaction},
author = {Opeyemi Abioye Ayodeji and Stephen Prior and Trevor Thomas and Peter Saddington and Sarvapali Ramchurn},
editor = {Tomayess Issa and Piet Kommers and Theodora Issa and Pedro Isa'ias and Touma B. Issa},
url = {https://eprints.soton.ac.uk/406888/},
year = {2017},
date = {2017-03-01},
booktitle = {Smart Technology Applications in Business Environments},
pages = {39–62},
publisher = {IGI Global},
abstract = {This chapter discusses HCI interfaces used in controlling aerial robotic systems (otherwise known as aerobots). The autonomy control level of aerobot is also discussed. However, due to the limitations of existing models, a novel classification model of autonomy, specifically designed for multirotor aerial robots, called the navigation control autonomy (nCA) model is also developed. Unlike the existing models such as the AFRL and ONR, this model is presented in tiers and has a two-dimensional pyramidal structure. This model is able to identify the control void existing beyond tier-one autonomy components modes and to map the upper and lower limits of control interfaces. Two solutions are suggested for dealing with the existing control void and the limitations of the RC joystick controller ? the multimodal HHI-like interface and the unimodal BCI interface. In addition to these, some human factors based performance measurement is recommended, and the plans for further works presented.},
keywords = {},
pubstate = {published},
tppubtype = {incollection}
}
This chapter discusses HCI interfaces used in controlling aerial robotic systems (otherwise known as aerobots). The autonomy control level of aerobot is also discussed. However, due to the limitations of existing models, a novel classification model of autonomy, specifically designed for multirotor aerial robots, called the navigation control autonomy (nCA) model is also developed. Unlike the existing models such as the AFRL and ONR, this model is presented in tiers and has a two-dimensional pyramidal structure. This model is able to identify the control void existing beyond tier-one autonomy components modes and to map the upper and lower limits of control interfaces. Two solutions are suggested for dealing with the existing control void and the limitations of the RC joystick controller ? the multimodal HHI-like interface and the unimodal BCI interface. In addition to these, some human factors based performance measurement is recommended, and the plans for further works presented.
86.
Bistaffa, Jesús Cerquides Alessandro Farinelli Filippo; Ramchurn, Sarvapali D.
Algorithms for Graph-Constrained Coalition Formation in the Real World Journal Article
In: ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 4, 2017.
@article{bistaffaetal2017b,
title = {Algorithms for Graph-Constrained Coalition Formation in the Real World},
author = {Jesús Cerquides Alessandro Farinelli Filippo Bistaffa and Sarvapali D. Ramchurn},
url = {http://www.sramchurn.com/wp-content/uploads/2017/03/2017tist.pdf},
doi = {http://dx.doi.org/10.1145/3040967},
year = {2017},
date = {2017-02-11},
journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
volume = {8},
number = {4},
keywords = {},
pubstate = {published},
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}
87.
Chalkiadakis, Sarvapali Alessandro Farinelli; Ramchurn Filippo Bistaffa Georgios
A Cooperative Game-Theoretic Approach to the Social Ridesharing Problem Journal Article
In: Artificial Intelligence Journal, pp. (accepted), 2017.
@article{bistaffa:etal:2017b,
title = {A Cooperative Game-Theoretic Approach to the Social Ridesharing Problem},
author = {Sarvapali Alessandro Farinelli; Ramchurn Filippo Bistaffa Georgios Chalkiadakis},
url = {http://www.sciencedirect.com/science/article/pii/S0004370217300243},
year = {2017},
date = {2017-02-11},
journal = {Artificial Intelligence Journal},
pages = {(accepted)},
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88.
Farinelli, Alessandro; Bicego, Manuele; Bistaffa, Filippo; Ramchurn, Sarvapali D.
A Hierarchical Clustering Approach to Large-scale Near-optimal Coalition Formation with Quality Guarantees Journal Article
In: Engineering Applications of Artificial Intelligence (EAAI), vol. 57, pp. 170-185, 2017.
@article{farinelli:etal:2017,
title = {A Hierarchical Clustering Approach to Large-scale Near-optimal Coalition Formation with Quality Guarantees},
author = {Alessandro Farinelli and Manuele Bicego and Filippo Bistaffa and Sarvapali D. Ramchurn},
url = {http://www.sramchurn.com/wp-content/uploads/2017/02/1-s2.0-S0952197616302536-main.pdf},
doi = {http://dx.doi.org/10.1016/j.engappai.2016.12.018},
year = {2017},
date = {2017-02-01},
journal = {Engineering Applications of Artificial Intelligence (EAAI)},
volume = {57},
pages = {170-185},
abstract = {Coalition formation is a fundamental approach to multi-agent coordination, and a key challenge in this context
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.},
keywords = {},
pubstate = {published},
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}
Coalition formation is a fundamental approach to multi-agent coordination, and a key challenge in this context
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.
is the coalition structure generation problem, where a set of agents must be partitioned into the best set of
coalitions. This problem is NP-hard and typical optimal algorithms do not scale to more than 50 agents: efficient
approximate solutions are therefore needed for hundreds or thousands of agents. In this paper we propose a
novel heuristic, based on ideas and tools used in the data clustering domain. In particular, we present a coalition
formation algorithm inspired by the well known class of hierarchical agglomerative clustering techniques
(Linkage algorithms). We present different variants of the algorithm, which we call Coalition Linkage (C-Link)
and demonstrate how such algorithm can be adapted to graph restricted coalition formation problems (where
an interaction graph defined among the agents restricts the set of feasible coalitions). Moreover, we discuss how
we can provide an upper bound on the value of the optimal coalition structure, and we show that for specific
characteristic functions we can provide such bounds while maintaining polynomial computational costs and
memory requirements. We empirically evaluate the different variants of the C-Link algorithm on two synthetic
benchmark data-sets, as well as in two real world scenarios, involving a collective energy purchasing and a ridesharing application. In these settings C-Link achieves promising results providing high quality solutions and
solving problem involving thousands of agents in few minutes.
89.
Cruz, Francisco; Espinosa, Antonio; Moure, Juan C.; Cerquides, Jesus; Rodriguez-Aguilar, Juan A.; Svensson, Kim; Ramchurn, Sarvapali D.
Coalition structure generation problems: optimization and parallelization of the IDP algorithm in multicore systems Journal Article
In: Concurrency and Computation: Practice and Experience, vol. 29, no. 5, pp. e3969–n/a, 2017, ISSN: 1532-0634, (e3969 cpe.3969).
@article{CPE:CPE3969,
title = {Coalition structure generation problems: optimization and parallelization of the IDP algorithm in multicore systems},
author = {Francisco Cruz and Antonio Espinosa and Juan C. Moure and Jesus Cerquides and Juan A. Rodriguez-Aguilar and Kim Svensson and Sarvapali D. Ramchurn},
url = {http://dx.doi.org/10.1002/cpe.3969},
doi = {10.1002/cpe.3969},
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journal = {Concurrency and Computation: Practice and Experience},
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note = {e3969 cpe.3969},
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90.
Ramchurn, Sarvapali; Simpson, Edwin; Fischer, Joel; Huynh, Trung Dong; Ikuno, Yuki; Reece, Steven; Jiang, Wenchao; Wu, Feng; Flann, Jack; Roberts, S. J.; Moreau, Luc; Rodden, T.; Jennings, N. R.
A Disaster Response System based on Human-Agent Collectives Journal Article
In: Journal of Artificial Intelligence Research, vol. 57, pp. 661-708, 2016.
@article{eps374070b,
title = {A Disaster Response System based on Human-Agent Collectives},
author = {Sarvapali Ramchurn and Edwin Simpson and Joel Fischer and Trung Dong Huynh and Yuki Ikuno and Steven Reece and Wenchao Jiang and Feng Wu and Jack Flann and S. J. Roberts and Luc Moreau and T. Rodden and N. R. Jennings},
url = {http://www.jair.org/media/5098/live-5098-9699-jair.pdf},
year = {2016},
date = {2016-12-01},
journal = {Journal of Artificial Intelligence Research},
volume = {57},
pages = {661-708},
abstract = {Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks pose significant challenges for emergency responders. First, they have to develop an understanding of the unfolding event either using their own resources or through third-parties such as the local population and agencies. Second, based on the information gathered, they need to deploy their teams in a flexible manner, ensuring that each team performs tasks in The most effective way. Third, given the dynamic nature of a disaster space, and the uncertainties involved in performing rescue missions, information about the disaster space and the actors within it needs to be managed to ensure that responders are always acting on up-to-date and trusted information. Against this background, this paper proposes a novel disaster response system called HAC-ER. Thus HAC-ER interweaves humans and agents, both robotic and software, in social relationships that augment their individual and collective capabilities. To design HAC-ER, we involved end-users including both experts and volunteers in a several participatory design workshops, lab studies, and field trials of increasingly advanced prototypes of individual components of HAC-ER as well as the overall system. This process generated a number of new quantitative and qualitative results but also raised a number of new research questions. HAC-ER thus demonstrates how such Human-Agent Collectives (HACs) can address key challenges in disaster response. Specifically, we show how HAC-ER utilises crowdsourcing combined with machine learning to obtain most important situational awareness from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments, as well as task planning for responders on the ground. Finally, HAC-ER incorporates an infrastructure and the associated intelligence for tracking and utilising the provenance of information shared across the entire system to ensure its accountability. We individually validate each of these elements of HAC-ER and show how they perform against standard (non-HAC) baselines and also elaborate on the evaluation of the overall system.},
keywords = {},
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}
Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks pose significant challenges for emergency responders. First, they have to develop an understanding of the unfolding event either using their own resources or through third-parties such as the local population and agencies. Second, based on the information gathered, they need to deploy their teams in a flexible manner, ensuring that each team performs tasks in The most effective way. Third, given the dynamic nature of a disaster space, and the uncertainties involved in performing rescue missions, information about the disaster space and the actors within it needs to be managed to ensure that responders are always acting on up-to-date and trusted information. Against this background, this paper proposes a novel disaster response system called HAC-ER. Thus HAC-ER interweaves humans and agents, both robotic and software, in social relationships that augment their individual and collective capabilities. To design HAC-ER, we involved end-users including both experts and volunteers in a several participatory design workshops, lab studies, and field trials of increasingly advanced prototypes of individual components of HAC-ER as well as the overall system. This process generated a number of new quantitative and qualitative results but also raised a number of new research questions. HAC-ER thus demonstrates how such Human-Agent Collectives (HACs) can address key challenges in disaster response. Specifically, we show how HAC-ER utilises crowdsourcing combined with machine learning to obtain most important situational awareness from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments, as well as task planning for responders on the ground. Finally, HAC-ER incorporates an infrastructure and the associated intelligence for tracking and utilising the provenance of information shared across the entire system to ensure its accountability. We individually validate each of these elements of HAC-ER and show how they perform against standard (non-HAC) baselines and also elaborate on the evaluation of the overall system.
91.
Garcia, Pedro Garcia; Costanza, Enrico; Verame, Jhim; Ramchurn, Sarvapali D.
The potential of physical motion cues: changing people?s perception of robots? performance Proceedings Article
In: UbiComp 2016: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, ACM, 2016.
@inproceedings{eps398009,
title = {The potential of physical motion cues: changing people?s perception of robots? performance},
author = {Pedro Garcia Garcia and Enrico Costanza and Jhim Verame and Sarvapali D. Ramchurn},
url = {http://eprints.soton.ac.uk/398009/},
year = {2016},
date = {2016-09-01},
booktitle = {UbiComp 2016: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing},
publisher = {ACM},
abstract = {Autonomous robotic systems can automatically perform actions on behalf of users in the domestic environment to help people in their daily activities. Such systems aim to reduce users' cognitive and physical workload, and improve wellbeing. While the benefits of these systems are clear, recent studies suggest that users may misconstrue their performance of tasks. We see an opportunity in designing interaction techniques that improve how users perceive the performance of such systems. We report two lab studies (N=16 each) designed to investigate whether showing physical motion, which is showing the process of a system through movement (that is intrinsic to the system's task), of an autonomous system as it completes its task, affects how users perceive its performance. To ensure our studies are ecologically valid and to motivate participants to provide thoughtful responses we adopted consensus-oriented financial incentives. Our results suggest that physical presence does yield higher performance ratings.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Autonomous robotic systems can automatically perform actions on behalf of users in the domestic environment to help people in their daily activities. Such systems aim to reduce users' cognitive and physical workload, and improve wellbeing. While the benefits of these systems are clear, recent studies suggest that users may misconstrue their performance of tasks. We see an opportunity in designing interaction techniques that improve how users perceive the performance of such systems. We report two lab studies (N=16 each) designed to investigate whether showing physical motion, which is showing the process of a system through movement (that is intrinsic to the system's task), of an autonomous system as it completes its task, affects how users perceive its performance. To ensure our studies are ecologically valid and to motivate participants to provide thoughtful responses we adopted consensus-oriented financial incentives. Our results suggest that physical presence does yield higher performance ratings.
92.
Truong, Ngoc Cuong; Baarslag, Tim; Ramchurn, Sarvapali D.; Tran-Thanh, Long
Interactive scheduling of appliance usage in the home Proceedings Article
In: 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 869–875, 2016.
@inproceedings{eps396670,
title = {Interactive scheduling of appliance usage in the home},
author = {Ngoc Cuong Truong and Tim Baarslag and Sarvapali D. Ramchurn and Long Tran-Thanh},
url = {http://eprints.soton.ac.uk/396670/},
year = {2016},
date = {2016-07-12},
booktitle = {25th International Joint Conference on Artificial Intelligence (IJCAI-16)},
pages = {869–875},
abstract = {We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user?s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real?world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We address the problem of recommending an appliance usage schedule to the homeowner which balances between maximising total savings and maintaining sufficient user convenience. An important challenge within this problem is how to elicit the the user preferences with low intrusiveness, in order to identify new schedules with high cost savings, that still lies within the user?s comfort zone. To tackle this problem we propose iDR, an interactive system for generating personalised appliance usage scheduling recommendations that maximise savings and convenience with minimal intrusiveness. In particular, our system learns when to stop interacting with the user during the preference elicitation process, in order to keep the bother cost (e.g., the amount of time the user spends, or the cognitive cost of interacting) minimal. We demonstrate through extensive empirical evaluation on real?world data that our approach improves savings by up to 35%, while maintaining a significantly lower bother cost, compared to state-of the-art benchmarks
93.
Baker, Chris; Ramchurn, Sarvapali D.; Teacy, Luke; Jennings, Nicholas
Planning search and rescue missions for UAV teams Proceedings Article
In: PAIS 2016: Conference on Prestigious Applications of Intelligent Systems at ECAI 2016, 2016.
@inproceedings{eps396996,
title = {Planning search and rescue missions for UAV teams},
author = {Chris Baker and Sarvapali D. Ramchurn and Luke Teacy and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/396996/},
year = {2016},
date = {2016-06-01},
booktitle = {PAIS 2016: Conference on Prestigious Applications of Intelligent Systems at ECAI 2016},
abstract = {The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out aerial surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. To aid in this process, it is desirable to exploit the increasing availability of data about a disaster from sources such as crowd reports, satellite re- mote sensing, or manned reconnaissance. In particular, such information can be a valuable resource to drive the planning of UAV flight paths over a space in order to discover people who are in danger. However challenges of computational tractability remain when planning over the very large action spaces that result. To overcome these, we introduce the survivor discovery problem and present as our solution, the first example of a continuous factored coordinated Monte Carlo tree search algorithm. Our evaluation against state of the art benchmarks show that our algorithm, Co-CMCTS, is able to localise more casualties faster than standard approaches by 7% or more on simulations with real-world data.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out aerial surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. To aid in this process, it is desirable to exploit the increasing availability of data about a disaster from sources such as crowd reports, satellite re- mote sensing, or manned reconnaissance. In particular, such information can be a valuable resource to drive the planning of UAV flight paths over a space in order to discover people who are in danger. However challenges of computational tractability remain when planning over the very large action spaces that result. To overcome these, we introduce the survivor discovery problem and present as our solution, the first example of a continuous factored coordinated Monte Carlo tree search algorithm. Our evaluation against state of the art benchmarks show that our algorithm, Co-CMCTS, is able to localise more casualties faster than standard approaches by 7% or more on simulations with real-world data.
94.
Fisher, Joel; Crabtree, Andy; Rodden, Tom; Colley, James; Costanza, Enrico; Jewell, Michael; Ramchurn, Sarvapali
"Just whack it on until it gets hot, then turn it off": Working with IoT Data in the Home Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385056,
title = {"Just whack it on until it gets hot, then turn it off": Working with IoT Data in the Home},
author = {Joel Fisher and Andy Crabtree and Tom Rodden and James Colley and Enrico Costanza and Michael Jewell and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/385056/},
year = {2016},
date = {2016-05-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
95.
Zhao, Dengji; Ramchurn, Sarvapali D.; Jennings, Nicholas
Fault tolerant mechanism design for general task allocation Proceedings Article
In: The 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), International Foundation for Autonomous Agents and Multiagent Systems, 2016.
@inproceedings{eps388365,
title = {Fault tolerant mechanism design for general task allocation},
author = {Dengji Zhao and Sarvapali D. Ramchurn and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/388365/},
year = {2016},
date = {2016-05-01},
booktitle = {The 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016)},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
abstract = {We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an allocation that maximises social welfare while taking their execution uncertainty into account (i.e., fault tolerant). To achieve this, we show that the post-execution verification (PEV)-based mechanism presented by Porter et al. (2008) is applicable if and only if agents' valuations are risk-neutral (i.e., the solution is almost universal). We then consider a more advanced setting where an agent's execution uncertainty is not completely predictable by the agent alone but aggregated from all agents' private opinions (known as trust). We show that PEV-based mechanism with trust is still applicable if and only if the trust aggregation is multilinear. Given this characterisation, we further demonstrate how this mechanism can be successfully applied in a real-world setting. Finally, we draw the parallels between our results and the literature of efficient mechanism design with general interdependent valuations.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We study a general task allocation problem, involving multiple agents that collaboratively accomplish tasks and where agents may fail to successfully complete the tasks assigned to them (known as execution uncertainty). The goal is to choose an allocation that maximises social welfare while taking their execution uncertainty into account (i.e., fault tolerant). To achieve this, we show that the post-execution verification (PEV)-based mechanism presented by Porter et al. (2008) is applicable if and only if agents' valuations are risk-neutral (i.e., the solution is almost universal). We then consider a more advanced setting where an agent's execution uncertainty is not completely predictable by the agent alone but aggregated from all agents' private opinions (known as trust). We show that PEV-based mechanism with trust is still applicable if and only if the trust aggregation is multilinear. Given this characterisation, we further demonstrate how this mechanism can be successfully applied in a real-world setting. Finally, we draw the parallels between our results and the literature of efficient mechanism design with general interdependent valuations.
96.
Wu, Feng; Ramchurn, Sarvapali D.; Chen, Xiaoping
Coordinating human-UAV teams in disaster response Proceedings Article
In: International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 524–530, 2016.
@inproceedings{eps393725,
title = {Coordinating human-UAV teams in disaster response},
author = {Feng Wu and Sarvapali D. Ramchurn and Xiaoping Chen},
url = {http://eprints.soton.ac.uk/393725/},
year = {2016},
date = {2016-04-01},
booktitle = {International Joint Conference on Artificial Intelligence (IJCAI-16)},
pages = {524–530},
abstract = {We consider a disaster response scenario where emergency responders have to complete rescue tasks in dynamic and uncertain environment with the assistance of multiple UAVs to collect information about the disaster space. To capture the uncertainty and partial observability of the domain, we model this problem as a POMDP. However, the resulting model is computationally intractable and cannot be solved by most existing POMDP solvers due to the large state and action spaces. By exploiting the problem structure we propose a novel online planning algorithm to solve this model. Specifically, we generate plans for the responders based on Monte-Carlo simulations and compute actions for the UAVs according to the value of information. Our empirical results confirm that our algorithm significantly outperforms the state-of-the-art both in time and solution quality.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
We consider a disaster response scenario where emergency responders have to complete rescue tasks in dynamic and uncertain environment with the assistance of multiple UAVs to collect information about the disaster space. To capture the uncertainty and partial observability of the domain, we model this problem as a POMDP. However, the resulting model is computationally intractable and cannot be solved by most existing POMDP solvers due to the large state and action spaces. By exploiting the problem structure we propose a novel online planning algorithm to solve this model. Specifically, we generate plans for the responders based on Monte-Carlo simulations and compute actions for the UAVs according to the value of information. Our empirical results confirm that our algorithm significantly outperforms the state-of-the-art both in time and solution quality.
97.
Baker, Chris; Ramchurn, Gopal; Teacy, Luke; Jennings, Nicholas
Factored Monte-Carlo tree search for coordinating UAVs in disaster response Proceedings Article
In: Distributed and Multi-Agent Planning, ICAPS, 2016.
@inproceedings{eps393649,
title = {Factored Monte-Carlo tree search for coordinating UAVs in disaster response},
author = {Chris Baker and Gopal Ramchurn and Luke Teacy and Nicholas Jennings},
url = {http://eprints.soton.ac.uk/393649/},
year = {2016},
date = {2016-04-01},
booktitle = {Distributed and Multi-Agent Planning},
publisher = {ICAPS},
abstract = {The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. However, an increase in the availability of real-time data about a disaster from sources such as crowd reports or satellites presents a valuable source of information to drive the planning of UAV flight paths over a space in order to discover people who are in danger. Nevertheless challenges remain when planning over the very large action spaces that result. To this end, we introduce the survivor discovery problem and present as our solution, the first example of a factored coordinated Monte Carlo tree search algorithm to perform decentralised path planning for multiple coordinated UAVs. Our evaluation against standard benchmarks show that our algorithm, Co-MCTS, is able to find more casualties faster than standard approaches by 10% or more on simulations with real-world data from the 2010 Haiti earthquake.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The coordination of multiple Unmanned Aerial Vehicles (UAVs) to carry out surveys is a major challenge for emergency responders. In particular, UAVs have to fly over kilometre-scale areas while trying to discover casualties as quickly as possible. However, an increase in the availability of real-time data about a disaster from sources such as crowd reports or satellites presents a valuable source of information to drive the planning of UAV flight paths over a space in order to discover people who are in danger. Nevertheless challenges remain when planning over the very large action spaces that result. To this end, we introduce the survivor discovery problem and present as our solution, the first example of a factored coordinated Monte Carlo tree search algorithm to perform decentralised path planning for multiple coordinated UAVs. Our evaluation against standard benchmarks show that our algorithm, Co-MCTS, is able to find more casualties faster than standard approaches by 10% or more on simulations with real-world data from the 2010 Haiti earthquake.
98.
Verame, Jhim Kiel M.; Costanza, Enrico; Ramchurn, Sarvapali
The Effect of Displaying System Confidence Information on the Usage of Autonomous Systems for Non-specialist Applications: A Lab Study Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385069b,
title = {The Effect of Displaying System Confidence Information on the Usage of Autonomous Systems for Non-specialist Applications: A Lab Study},
author = {Jhim Kiel M. Verame and Enrico Costanza and Sarvapali Ramchurn},
url = {http://eprints.soton.ac.uk/385069/},
year = {2016},
date = {2016-01-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
abstract = {Autonomous systems are designed to take actions on behalf of users, acting autonomously upon data from sensors or online sources. As such, the design of interaction mechanisms that enable users to understand the operation of autonomous systems and flexibly delegate or regain control is an open challenge for HCI. Against this background, in this paper we report on a lab study designed to investigate whether displaying the confidence of an autonomous system about the quality of its work, which we call its confidence information, can improve user acceptance and interaction with autonomous systems. The results demonstrate that confidence information encourages the usage of the autonomous system we tested, compared to a situation where such information is not available. Furthermore, an additional contribution of our work is the methodology we employ to study users' incentives to do work in collaboration with the autonomous system. In experiments comparing different incentive strategies, our results indicate that our translation of behavioural economics research methods to HCI can support the study of interactions with autonomous systems in the lab.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Autonomous systems are designed to take actions on behalf of users, acting autonomously upon data from sensors or online sources. As such, the design of interaction mechanisms that enable users to understand the operation of autonomous systems and flexibly delegate or regain control is an open challenge for HCI. Against this background, in this paper we report on a lab study designed to investigate whether displaying the confidence of an autonomous system about the quality of its work, which we call its confidence information, can improve user acceptance and interaction with autonomous systems. The results demonstrate that confidence information encourages the usage of the autonomous system we tested, compared to a situation where such information is not available. Furthermore, an additional contribution of our work is the methodology we employ to study users' incentives to do work in collaboration with the autonomous system. In experiments comparing different incentive strategies, our results indicate that our translation of behavioural economics research methods to HCI can support the study of interactions with autonomous systems in the lab.
99.
Alan, Alper Turan; Shann, Mike; Costanza, Enrico; Ramchurn, Sarvapali; Seuken, Sven
It is too hot: an in-situ study of three designs for heating Proceedings Article
In: The SIGCHI Conference on Human Factors in Computing Systems, 2016.
@inproceedings{eps385045b,
title = {It is too hot: an in-situ study of three designs for heating},
author = {Alper Turan Alan and Mike Shann and Enrico Costanza and Sarvapali Ramchurn and Sven Seuken},
url = {http://eprints.soton.ac.uk/385045/},
year = {2016},
date = {2016-01-01},
booktitle = {The SIGCHI Conference on Human Factors in Computing Systems},
abstract = {Smart technologies are becoming increasingly ubiquitous, and consequently transforming our lives. Domestic energy use is one of the most talked domain that people may greatly benefit from these technologies. Given this, it is important to understand interactions with smart systems within people?s everyday lives. To this end, we developed and deployed the first heating system that allows its users to control their home heating with real-time prices. In particular, we implemented three different designs of our heating system, and evaluated them with 30 UK households in a four-week in the wild study. Our findings through thematic analysis show that our participants formed different understandings and expectations of the system, and used it in various ways to effectively respond to real-time prices while maintaining their thermal comfort. These findings contribute to our understanding of interactions with smart energy systems and provide key design implications for developing them.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Smart technologies are becoming increasingly ubiquitous, and consequently transforming our lives. Domestic energy use is one of the most talked domain that people may greatly benefit from these technologies. Given this, it is important to understand interactions with smart systems within people?s everyday lives. To this end, we developed and deployed the first heating system that allows its users to control their home heating with real-time prices. In particular, we implemented three different designs of our heating system, and evaluated them with 30 UK households in a four-week in the wild study. Our findings through thematic analysis show that our participants formed different understandings and expectations of the system, and used it in various ways to effectively respond to real-time prices while maintaining their thermal comfort. These findings contribute to our understanding of interactions with smart energy systems and provide key design implications for developing them.
100.
Bandhyopadhyay, Sambaran; Narayanam, Ramasuri; Kumar, Pratyush; Ramchurn, Sarvapali Dyanand; Arya, Vijay
An Axiomatic Framework for Ex-Ante Dynamic Pricing Mechanisms in Smart Grid Proceedings Article
In: Proceedings of 30th AAAI Conference on Artificial Intelligence (AAAI), AAAI Press, 2016.
@inproceedings{eps386417,
title = {An Axiomatic Framework for Ex-Ante Dynamic Pricing Mechanisms in Smart Grid},
author = {Sambaran Bandhyopadhyay and Ramasuri Narayanam and Pratyush Kumar and Sarvapali Dyanand Ramchurn and Vijay Arya},
url = {http://eprints.soton.ac.uk/386417/},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of 30th AAAI Conference on Artificial Intelligence (AAAI)},
publisher = {AAAI Press},
abstract = {In electricity markets, the choice of the right pricing regime is crucial for the utilities because the price they charge to their consumers, in anticipation of their demand in real-time, is a key determinant of their profits and ultimately their survival in competitive energy markets. Among the existing pricing regimes, in this paper, we consider ex-ante dynamic pricing schemes as (i) they help to address the peak demand problem (a crucial problem in smart grids), and (ii) they are transparent and fair to consumers as the cost of electricity can be calculated before the actual consumption. In particular, we propose an axiomatic framework that establishes the conceptual underpinnings of the class of ex-ante dynamic pricing schemes.We first propose five key axioms that reflect the criteria that are vital for energy utilities and their relationship with consumers. We then prove an impossibility theorem to show that there is no pricing regime that satisfies all the five axioms simultaneously.We also study multiple cost functions arising from various pricing regimes to examine the subset of axioms that they satisfy. We believe that our proposed framework in this paper is first of its kind to evaluate the class of ex-ante dynamic pricing schemes in a manner that can be operationalised by energy utilities.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
In electricity markets, the choice of the right pricing regime is crucial for the utilities because the price they charge to their consumers, in anticipation of their demand in real-time, is a key determinant of their profits and ultimately their survival in competitive energy markets. Among the existing pricing regimes, in this paper, we consider ex-ante dynamic pricing schemes as (i) they help to address the peak demand problem (a crucial problem in smart grids), and (ii) they are transparent and fair to consumers as the cost of electricity can be calculated before the actual consumption. In particular, we propose an axiomatic framework that establishes the conceptual underpinnings of the class of ex-ante dynamic pricing schemes.We first propose five key axioms that reflect the criteria that are vital for energy utilities and their relationship with consumers. We then prove an impossibility theorem to show that there is no pricing regime that satisfies all the five axioms simultaneously.We also study multiple cost functions arising from various pricing regimes to examine the subset of axioms that they satisfy. We believe that our proposed framework in this paper is first of its kind to evaluate the class of ex-ante dynamic pricing schemes in a manner that can be operationalised by energy utilities.
Selected Publications
Multi-agent signal-less intersection management with dynamic platoon formation
No data available.
https://eprints.soton.ac.uk/478647/
@inproceedings{soton478647,
title = {Multi-agent signal-less intersection management with dynamic platoon formation},
author = {Phuriwat Worrawichaipat and Enrico Gerding and Ioannis Kaparias and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/478647/},
year = {2023},
date = {2023-05-01},
booktitle = {22nd International Conference on Autonomous Agents and Multiagent Systems (29/05/23 - 02/06/23)},
pages = {1542--1550},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
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title = {Multi-agent signal-less intersection management with dynamic platoon formation},
author = {Phuriwat Worrawichaipat and Enrico Gerding and Ioannis Kaparias and Sarvapali Ramchurn},
url = {https://eprints.soton.ac.uk/478647/},
year = {2023},
date = {2023-05-01},
booktitle = {22nd International Conference on Autonomous Agents and Multiagent Systems (29/05/23 - 02/06/23)},
pages = {1542--1550},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
AI Foundation Models: initial review, CMA Consultation, TAS Hub Response
No data available.
https://eprints.soton.ac.uk/477553/
@misc{soton477553,
title = {AI Foundation Models: initial review, CMA Consultation, TAS Hub Response},
author = {Joshua Krook and Derek McAuley and Stuart Anderson and John Downer and Peter Winter and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/477553/},
year = {2023},
date = {2023-06-01},
publisher = {University of Southampton},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
title = {AI Foundation Models: initial review, CMA Consultation, TAS Hub Response},
author = {Joshua Krook and Derek McAuley and Stuart Anderson and John Downer and Peter Winter and Sarvapali D Ramchurn},
url = {https://eprints.soton.ac.uk/477553/},
year = {2023},
date = {2023-06-01},
publisher = {University of Southampton},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
The effect of data visualisation quality and task density on human-swarm interaction
No data available.
https://eprints.soton.ac.uk/479970/
@inproceedings{soton479970,
title = {The effect of data visualisation quality and task density on human-swarm interaction},
author = {Ayodeji Abioye and Mohammad Naiseh and William Hunt and Jediah R Clark and Sarvapali D Ramchurn and Mohammad Soorati},
url = {https://eprints.soton.ac.uk/479970/},
year = {2023},
date = {2023-06-01},
booktitle = {Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
publisher = {IEEE},
abstract = {Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the simulation platform) as well as their workload and trust level (measured through a questionnaire after completing a human-swarm scenario). The findings from our study indicated that the group granted access to high-quality data exhibited an increased workload and placed greater trust in the swarm, thus confirming our initial hypothesis. However, we also found that the number of accurately identified casualties did not significantly vary between the two groups, suggesting that data quality had no impact on the successful completion of tasks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {The effect of data visualisation quality and task density on human-swarm interaction},
author = {Ayodeji Abioye and Mohammad Naiseh and William Hunt and Jediah R Clark and Sarvapali D Ramchurn and Mohammad Soorati},
url = {https://eprints.soton.ac.uk/479970/},
year = {2023},
date = {2023-06-01},
booktitle = {Proceedings of the 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},
publisher = {IEEE},
abstract = {Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-quality data can affect the performance of the human-swarm system - the number of tasks completed and the human trust level in operation. We designed an experiment where a human operator is tasked to operate a swarm to identify casualties in an area within a given time period. One group of operators had the option to request high-quality pictures while the other group had to base their decision on the available low-quality images. We performed a user study with 120 participants and recorded their success rate (directly logged via the simulation platform) as well as their workload and trust level (measured through a questionnaire after completing a human-swarm scenario). The findings from our study indicated that the group granted access to high-quality data exhibited an increased workload and placed greater trust in the swarm, thus confirming our initial hypothesis. However, we also found that the number of accurately identified casualties did not significantly vary between the two groups, suggesting that data quality had no impact on the successful completion of tasks.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Demonstrating performance benefits of human-swarm teaming
Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.
https://eprints.soton.ac.uk/479903/
@inproceedings{soton479903,
title = {Demonstrating performance benefits of human-swarm teaming},
author = {William Hunt and Jack Ryan and Ayodeji O Abioye and Sarvapali D Ramchurn and Mohammad D Soorati},
url = {https://eprints.soton.ac.uk/479903/},
year = {2023},
date = {2023-05-01},
booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
pages = {3062--3064},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
abstract = {Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
title = {Demonstrating performance benefits of human-swarm teaming},
author = {William Hunt and Jack Ryan and Ayodeji O Abioye and Sarvapali D Ramchurn and Mohammad D Soorati},
url = {https://eprints.soton.ac.uk/479903/},
year = {2023},
date = {2023-05-01},
booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
pages = {3062--3064},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
abstract = {Autonomous swarms of robots can bring robustness, scalability and adaptability to safety-critical tasks such as search and rescue but their application is still very limited. Using semi-autonomous swarms with human control can bring robot swarms to real-world applications. Human operators can define goals for the swarm, monitor their performance and interfere with, or overrule, the decisions and behaviour. We present the "Human And Robot Interactive Swarm'' simulator (HARIS) that allows multi-user interaction with a robot swarm and facilitates qualitative and quantitative user studies through simulation of robot swarms completing tasks, from package delivery to search and rescue, with varying levels of human control. In this demonstration, we showcase the simulator by using it to study the performance gain offered by maintaining a "human-in-the-loop'' over a fully autonomous system as an example. This is illustrated in the context of search and rescue, with an autonomous allocation of resources to those in need.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
0000
Bistaffa, Jesús Cerquides Alessandro Farinelli Filippo; Ramchurn, Sarvapali D.
Algorithms for Graph-Constrained Coalition Formation in the Real World Journal Article
In: ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 4, 0000.
@article{bistaffaetal2017,
title = {Algorithms for Graph-Constrained Coalition Formation in the Real World},
author = {Jesús Cerquides Alessandro Farinelli Filippo Bistaffa and Sarvapali D. Ramchurn},
doi = {http://dx.doi.org/10.1145/3040967},
journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},
volume = {8},
number = {4},
keywords = {},
pubstate = {published},
tppubtype = {article}
}