Publications

@inproceedings{DBLP:conf/ijcai/VuAR18,

title = {A Decentralised Approach to Intersection Traffic Management},

author = {Huan Vu and Samir Aknine and Sarvapali D Ramchurn},

url = {https://doi.org/10.24963/ijcai.2018/73},

doi = {10.24963/ijcai.2018/73},

year  = {2018},

date = {2018-01-01},

booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on 

 Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, 

 Sweden.},

pages = {527–533},

crossref = {DBLP:conf/ijcai/2018},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@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 = {autonomous computing, human collectives, IoT, Smart cities, wearable computing},

pubstate = {published},

tppubtype = {inproceedings}

}

@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 = {Alliances, Collective decision making, Groups, Multilaterale Negotiation},

pubstate = {published},

tppubtype = {inproceedings}

}

@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 = {Energy, human-agent collectives},

pubstate = {published},

tppubtype = {inproceedings}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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 = {execution uncertainty, interdependent valuations, trust aggregation, type verification},

pubstate = {published},

tppubtype = {inproceedings}

}

@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}

}

@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}

}

@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}

}

@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}

}

@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}

}

@inproceedings{cailliere:hal-01329606,

title = {Managing energy markets in future smart grids using bilateral contracts},

author = {Romain Calliere and Samir Aknine and Antoine Nongaillard and Sarvapali Ramchurn},

url = {https://hal.archives-ouvertes.fr/hal-01329606},

year  = {2016},

date = {2016-01-01},

booktitle = {European Conference on Artificial Intelligence (ECAI)},

address = {The Hague, Netherlands},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/smartgridcomm/KoufakisRBR16,

title = {Towards an optimal EV charging scheduling scheme with V2G and 

 V2V energy transfer},

author = {Alexandros - and Emmanouil S Rigas and Nick Bassiliades and Sarvapali D Ramchurn},

url = {https://doi.org/10.1109/SmartGridComm.2016.7778778},

doi = {10.1109/SmartGridComm.2016.7778778},

year  = {2016},

date = {2016-01-01},

booktitle = {2016 IEEE International Conference on Smart Grid Communications, 

 SmartGridComm 2016, Sydney, Australia, November 6-9, 2016},

pages = {302–307},

crossref = {DBLP:conf/smartgridcomm/2016},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps382948,

title = {CrowdAR: augmenting live video with a real-time crowd},

author = {Elliot Salisbury and Sebastian Stein and Sarvapali Ramchurn},

url = {http://eprints.soton.ac.uk/382948/},

year  = {2015},

date = {2015-11-01},

booktitle = {HCOMP 2015: Third AAAI Conference on Human Computation and Crowdsourcing},

abstract = {Finding and tracking targets and events in a live video feed is important for many commercial applications, from CCTV surveillance used by police and security firms, to the rapid mapping of events from aerial imagery. However, descriptions of targets are typically provided in natural language by the end users, and interpreting these in the context of a live video stream is a complex task. Due to current limitations in artificial intelligence, especially vision, this task cannot be automated and instead requires human supervision. Hence, in this paper, we consider the use of real-time crowdsourcing to identify and track targets given by a natural language description. In particular we present a novel method for augmenting live video with a real-time crowd.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{bistaffaetal2015,

title = {Recommending Fair Payments for Large-Scale Social Ridesharing},

author = {Alessandro Farinelli Georgios Chalkiadakis Filippo Bistaffa and Sarvapali D. Ramchurn},

url = {https://www.sramchurn.com/wp-content/uploads/2017/02/2015recsys.pdf},

year  = {2015},

date = {2015-09-16},

booktitle = {ACM Conference on Recommender Systems (Recsys)},

keywords = {Coalition Formation, mas, Ridesharing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps378696,

title = {Managing energy tariffs with agents: a field study of a future smart energy system at home},

author = {Alper T. Alan and Enrico Costanza and Sarvapali Ramchurn and Joel Fischer and Tom Rodden and N. R. Jennings},

url = {http://eprints.soton.ac.uk/378696/},

year  = {2015},

date = {2015-07-01},

booktitle = {Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps378696b,

title = {Managing energy tariffs with agents: a field study of a future smart energy system at home},

author = {Alper T. Alan and Enrico Costanza and Sarvapali Ramchurn and Joel Fischer and Tom Rodden and N. R. Jennings},

url = {http://eprints.soton.ac.uk/378696/},

year  = {2015},

date = {2015-07-01},

booktitle = {Adjunct Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers (Ubicomp)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{fischer:etal:2015,

title = {Building a Bird's Eye View: Collaborative Work},

author = {Tom Rodden Stuart Reeves Joel E. Fischer and David Jones},

url = {https://www.sramchurn.com/wp-content/uploads/2015/01/pn1018-fischerA.pdf},

year  = {2015},

date = {2015-05-01},

booktitle = {Proceedings of SIGCHI (To appear)},

keywords = {Disaster Management},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{tranh:Etal:2015,

title = {Crowdsourcing Complex Workflows under Budget Constraints},

author = {Avi Rosenfeld Trung Dong Huynh Long Tran-Thanh},

url = {http://eprints.soton.ac.uk/372107/},

year  = {2015},

date = {2015-01-25},

booktitle = {Proceedings of the AAAI Conference},

publisher = {AAAI},

abstract = {We consider the problem of task allocation in crowdsourc- ing systems with multiple complex workflows, each of which consists of a set of inter-dependent micro-tasks. We propose Budgeteer, an algorithm to solve this problem under a bud- get constraint. In particular, our algorithm first calculates an efficient way to allocate budget to each workflow. It then de- termines the number of inter-dependent micro-tasks and the price to pay for each task within each workflow, given the cor- responding budget constraints. We empirically evaluate it on a well-known crowdsourcing-based text correction workflow using Amazon Mechanical Turk, and show that Budgeteer can achieve similar levels of accuracy to current benchmarks, but is on average 45% cheaper.},

keywords = {Applications, crowdsourcing, human-agent collectives},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{bistaffa:etal:2015,

title = {Sharing Rides with Friends: a Coalition Formation Algorithm for Ridesharing},

author = {Sarvapali D. Ramchurn Alessandro Farinelli Filippo Bistaffa},

url = {http://eprints.soton.ac.uk/372048/},

year  = {2015},

date = {2015-01-25},

booktitle = {Proceedings of the AAAI Conference},

abstract = {We consider the Social Ridesharing (SR) problem, where a set of commuters, connected through a social network, ar- range one-time rides at a very short notice. In particular, we focus on the associated optimisation problem of forming cars to minimise the travel cost of the overall system mod- elling such problem as a graph constrained coalition forma- tion (GCCF) problem, where the set of feasible coalitions is restricted by a graph (i.e., the social network). Moreover, we significantly extend the state of the art algorithm for GCCF, i.e., the CFSS algorithm, to solve our GCCF model of the SR problem. Our empirical evaluation uses a real dataset for both spatial (GeoLife) and social data (Twitter), to validate the ap- plicability of our approach in a realistic application scenario. Empirical results show that our approach computes optimal solutions for systems of medium scale (up to 100 agents) providing significant cost reductions (up to −36.22%). More- over, we can provide approximate solutions for very large systems (i.e., up to 2000 agents) and good quality guarantees (i.e., with an approximation ratio of 1.41 in the worst case) within minutes (i.e., 100 seconds).},

keywords = {Coalition Formation, optimisation, Ridesharing, Social Networks},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zhao:etal:2015,

title = {Balanced Trade Reduction for Dual-Role Exchange Markets},

author = {Enrico H. Gerding Sarvapali D. Ramchurn Dengji Zhao and Nicholas R. Jennings},

url = {http://eprints.soton.ac.uk/372050/},

year  = {2015},

date = {2015-01-25},

booktitle = {Proceedings of the AAAI Conference},

abstract = {We consider dual-role exchange markets, where traders can offer to both buy and sell the same commodity in the exchange but, if they transact, they can only be either a buyer or a seller, which is determined by the market mechanism. To design desirable mechanisms for such exchanges, we show that existing solutions may not be incentive compatible, and more importantly, cause the market maker to suffer a significant deficit. Hence, to combat this problem, following McAfee’s trade reduc- tion approach, we propose a new trade reduction mech- anism, called balanced trade reduction, that is incen- tive compatible and also provides flexible trade-offs be- tween efficiency and deficit.},

keywords = {Electric Vehicles, Energy, Game Theory, mechanism design, Ridesharing},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps375287,

title = {Real-time opinion aggregation methods for crowd robotics},

author = {Elliot Salisbury and Sebastian Stein and Sarvapali Ramchurn},

url = {http://eprints.soton.ac.uk/375287/},

year  = {2015},

date = {2015-01-01},

booktitle = {Autonomous Agents and Multiagent Systems (AAMAS 2015)},

abstract = {Unmanned Aerial Vehicles (UAVs) are increasingly becoming instrumental to many commercial applications, such as transportation and maintenance. However, these applications require flexibility, understanding of natural language, and comprehension of video streams that cannot currently be automated and instead require the intelligence of a skilled human pilot. While having one pilot individually supervising a UAV is not scalable, the machine intelligence, especially vision, required to operate a UAV is still inadequate. Hence, in this paper, we consider the use of crowd robotics to harness a real-time crowd to orientate a UAV in an unknown environment. In particular, we present two novel real-time crowd input aggregation methods. To evaluate these methods, we develop a new testbed for crowd robotics, called CrowdDrone, that allows us to evaluate crowd robotic systems in a variety of scenarios. Using this platform, we benchmark our real-time aggregation methods with crowds hired from Amazon Mechanical Turk and show that our techniques outperform the current state-of-the-art aggregation methods, enabling a robotic agent to travel faster across a fixed distance, and with more precision. Furthermore, our aggregation methods are shown to be significantly more effective in dynamic scenarios},

keywords = {crowdsourcing, uav},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps374070,

title = {HAC-ER: 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://eprints.soton.ac.uk/374070/},

year  = {2015},

date = {2015-01-01},

booktitle = {14th International Conference on Autonomous Agents and Multi-Agent Systems},

abstract = {This paper proposes a novel disaster management system called HAC-ER that addresses some of the challenges faced by emer- gency responders by enabling humans and agents, using state-of- the-art algorithms, to collaboratively plan and carry out tasks in teams referred to as human-agent collectives. In particular, HAC- ER utilises crowdsourcing combined with machine learning to ex- tract situational awareness information from large streams of re- ports 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 a tool for tracking and analysing the provenance of information shared across the entire system. In summary, this paper describes a pro- totype system, validated by real-world emergency responders, that combines several state-of-the-art techniques for integrating humans and agents, and illustrates, for the first time, how such an approach can enable more effective disaster response operations.},

keywords = {Coordination, crowdsourcing, human-agent collectives, human-agent interaction, multi-agent systems, uav},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps376618,

title = {A scalable, decentralised multi-issue negotiation protocol for energy exchange},

author = {Muddasser Alam and Enrico H. Gerding and Alex Rogers and Sarvapali D. Ramchurn},

url = {http://eprints.soton.ac.uk/376618/},

year  = {2015},

date = {2015-01-01},

booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},

abstract = {We present a novel negotiation protocol to facilitate energy exchange between off-grid homes that are equipped with renewable energy generation and electricity storage. Our protocol imposes restrictions over negotiation such that it reduces the complex interdependent multi-issue negotiation to one where agents have a strategy profile in subgame perfect Nash equilibrium. We show that our protocol is concurrent, scalable and; under certain conditions; leads to Pareto-optimal outcomes.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps377186,

title = {Agile Planning for Real-World Disaster Response},

author = {Feng Wu and Sarvapali Ramchurn and Wenchao Jiang and Joel Fischer and Tom Rodden and Nicholas R. Jennings},

url = {http://eprints.soton.ac.uk/377186/},

year  = {2015},

date = {2015-01-01},

booktitle = {International Joint Conference on Artificial Intelligence},

abstract = {We consider a setting where an agent-based planner instructs teams of human emergency responders to perform tasks in the real world. Due to uncertainty in the environment and the inability of the planner to consider all human preferences and all attributes of the real-world, humans may reject plans computed by the agent. A na??ve solution that replans given a rejection is inefficient and does not guarantee the new plan will be acceptable. Hence, we propose a new model re-planning problem using a Multi-agent Markov Decision Process that integrates potential rejections as part of the planning process and propose a novel algorithm to efficiently solve this new model. We empirically evaluate our algorithm and show that it outperforms current benchmarks. Our algorithm is also shown to perform better in pilot studies with real humans.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps377185,

title = {A Study of Human-Agent Collaboration for Multi-UAV Task Allocation in Dynamic Environments},

author = {Sarvapali Ramchurn and Joel Fischer and Yuki Ikuno and Feng Wu and Jack Flann and Antony Waldock},

url = {http://eprints.soton.ac.uk/377185/},

year  = {2015},

date = {2015-01-01},

booktitle = {International Joint Conference on Artificial Intelligence},

abstract = {We consider a setting where a team of humans oversee the coordination of multiple Unmanned Aerial Vehicles (UAVs) to perform a number of search tasks in dynamic environments that may cause the UAVs to drop out. Hence, we develop a set of multi-UAV supervisory control interfaces and a multi-agent coordination algorithm to support human decision making in this setting. To elucidate the resulting interactional issues, we compare manual and mixed-initiative task allocation in both static and dynamic environments in lab studies with 40 participants and observe that our mixed-initiative system results in lower workloads and better performance in re-planning tasks than one which only involves manual task allocation. Our analysis points to new insights into the way humans appropriate flexible autonomy.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Holyhead:2015:CTR:2768510.2768531,

title = {Consumer Targeting in Residential Demand Response Programmes},

author = {James C. Holyhead and Sarvapali D. Ramchurn and Alex Rogers},

url = {http://doi.acm.org/10.1145/2768510.2768531},

isbn = {978-1-4503-3609-3},

year  = {2015},

date = {2015-01-01},

booktitle = {Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems},

pages = {7–16},

publisher = {ACM},

address = {Bangalore, India},

series = {e-Energy '15},

keywords = {Energy, optimisation, smart grid},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps360820,

title = {A field study of human-agent interaction for electricity tariff switching},

author = {Alper Alan and Enrico Costanza and J. Fischer and Sarvapali Ramchurn and T. Rodden and N. R. Jennings},

url = {http://eprints.soton.ac.uk/360820/},

year  = {2014},

date = {2014-01-01},

booktitle = {Proceedings of the 13th International Conference on Autonomous Agents and Multi-Agent Systems},

abstract = {Recently, many algorithms have been developed for autonomous agents to manage home energy use on behalf of their human owners. By so doing, it is expected that agents will be more efficient at, for example, choosing the best energy tariff to switch to when dynamically priced tariffs come about. However, to date, there has been no validation of such technologies in any field trial. In particular, it has not been shown whether users prefer fully autonomous agents as opposed to controlling their preferences manually. Hence, in this paper we describe a novel platform, called Tariff Agent, to study notions of flexible autonomy in the context of tariff switching. Tariff Agent uses real-world datasets and real-time electricity monitoring to instantiate a scenario where human participants may have to make, or delegate to their agent (in different ways), tariff switching decisions given uncertainties about their own consumption and tariff prices. We carried out a field trial with 10 participants and, from both quantitative and qualitative results, formulate novel design guidelines for systems that implement flexible autonom.},

keywords = {electricity, Energy, hai, hci, human-agent interaction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps361173,

title = {Doing the laundry with agents: a field trial of a future smart energy system in the home},

author = {Enrico Costanza and Joel E Fischer and James A Colley and Tom Rodden and Sarvapali Ramchurn and Nicholas R. Jennings},

url = {http://eprints.soton.ac.uk/361173/},

year  = {2014},

date = {2014-01-01},

booktitle = {ACM CHI Conference on Human Factors in Computing Systems 2014},

pages = {813–822},

organization = {ACM},

keywords = {Energy, hai},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{eps362321,

title = {BudgetFix: budget limited crowdsourcing for interdependent task allocation with quality guarantees},

author = {Long Tran-Thanh and Trung Dong Huynh and A Rosenfield and Sarvapali Ramchurn and Nicholas R. Jennings},

url = {http://eprints.soton.ac.uk/362321/},

year  = {2014},

date = {2014-01-01},

booktitle = {13th International Conference on Autonomous Agents and Multi-Agent Systems},

publisher = {International Foundation for Autonomous Agents and Multiagent Systems},

keywords = {hai, mas},

pubstate = {published},

tppubtype = {inproceedings}

}

@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},

urldate = {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}

}

@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},

urldate = {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}

}

@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},

urldate = {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}

}

@inproceedings{soton471260,

title = {Revisiting deep fisher vectors: using fisher information to improve object classification},

author = {Sarah Ahmed and Tayyaba Azim and Joseph Arthur Early and Sarvapali Ramchurn},

url = {https://eprints.soton.ac.uk/471260/},

year  = {2022},

date = {2022-11-01},

booktitle = {British Machine Vision Conference (21/11/22 - 24/11/22)},

abstract = {Although deep learning models have become the gold standard in achieving outstanding results on a large variety of computer vision and machine learning tasks, the use of kernel methods has still not gone out of trend because of its potential to beat deep learning performances at a number of occasions. Given the potential of kernel techniques, prior works have also proposed the use of hybrid approaches combining deep learning with kernel learning to complement their respective strengths and weaknesses. This work develops this idea further by introducing an improved version of Fisher kernels derived from the deep Boltzmann machines (DBM). Our improved deep Fisher kernel (IDFK) utilises an approximation of the Fisher information matrix to derive improved Fisher vectors. We show IDFK can be utilised to retain a high degree of class separability, making it appropriate for classification and retrieval tasks. The efficacy of the proposed approach is evaluated on three benchmark data sets: MNIST, USPS and Alphanumeric, showing an improvement in classification performance over existing kernel approaches, and comparable performance to deep learning methods, but with much reduced computational costs. Using explainable AI methods, we also demonstrate why our IDFK leads to better classification performance.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{soton456716,

title = {An agent-based simulator for maritime transport decarbonisation: Demonstration track},

author = {Jan Buermann and Dimitar Georgiev and Enrico Gerding and Lewis Hill and Obaid Malik and Alexandru Pop and Matthew Pun and Sarvapali Ramchurn and Elliot Salisbury and Ivan Stojanovic},

url = {https://eprints.soton.ac.uk/456716/},

year  = {2022},

date = {2022-05-01},

booktitle = {21st International Conference on Autonomous Agents and Multiagent Systems (09/05/22 - 13/05/22)},

pages = {1890–1892},

abstract = {Greenhouse gas (GHG) emission reduction is an important and necessary goal; currently, different policies to reduce GHG emissions in maritime transport are being discussed. Amongst policies, like carbon taxes or carbon intensity targets, it is hard to determine which policies can successfully reduce GHG emissions while allowing the industry to be profitable. We introduce an agent-based maritime transport simulator to investigate the effectiveness of two decarbonisation policies by simulating a maritime transport operator?s trade pattern and fleet make-up changes as a reaction to taxation and fixed targets. This first of its kind simulator allows to compare and quantify the difference of carbon reduction policies and how they affect shipping operations.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{soton454952,

title = {Model agnostic interpretability for multiple instance learning},

author = {Joseph Early and Christine Evers and Sarvapali Ramchurn},

url = {https://eprints.soton.ac.uk/454952/},

year  = {2022},

date = {2022-01-01},

booktitle = {International Conference on Learning Representations 2022 (25/04/22 - 29/04/22)},

abstract = {In Multiple Instance Learning (MIL), models are trained using bags of instances, where only a single label is provided for each bag. A bag label is often only determined by a handful of key instances within a bag, making it difficult to interpret what information a classifier is using to make decisions. In this work, we establish the key requirements for interpreting MIL models. We then go on to develop several model-agnostic approaches that meet these requirements. Our methods are compared against existing inherently interpretable MIL models on several datasets, and achieve an increase in interpretability accuracy of up to 30%. We also examine the ability of the methods to identify interactions between instances and scale to larger datasets, improving their applicability to real-world problems.},

note = {25 pages (9 content, 2 acknowledgement + references, 14 appendix). 16 figures (3 main content, 13 appendix). Submitted and accepted to ICLR 22, see http://openreview.net/forum?id=KSSfF5lMIAg . Revision: added additional acknowledgements},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}