@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}
}
@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}
}
@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}
}
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}
}
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.
http://eprints.soton.ac.uk/393725/
@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}
}
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.
http://eprints.soton.ac.uk/393649/
@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}
}
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.
http://eprints.soton.ac.uk/385069/
@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}
}
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.
http://eprints.soton.ac.uk/385045/
@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}
}
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.
http://eprints.soton.ac.uk/386417/
@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{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}
}
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