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Issue title: Multi-agent systems research in the United Kingdom
Guest editors: Stefano V. Albrecht and Michael Woolridge
Article type: Research Article
Authors: Lacerda, Bruno; * | Gautier, Anna | Rutherford, Alex | Stephens, Alex | Street, Charlie | Hawes, Nick
Affiliations: Oxford Robotics Institute, University of Oxford, United Kingdom
Correspondence: [*] Corresponding author. E-mail: bruno@robots.ox.ac.uk.
Abstract: In this overview paper, we present the work of the Goal-Oriented Long-Lived Systems Lab on multi-robot systems. We address multi-robot systems from a decision-making under uncertainty perspective, proposing approaches that explicitly reason about the inherent uncertainty of action execution, and how such stochasticity affects multi-robot coordination. To develop effective decision-making approaches, we take a special focus on (i) temporal uncertainty, in particular of action execution; (ii) the ability to provide rich guarantees of performance, both at a local (robot) level and at a global (team) level; and (iii) scaling up to systems with real-world impact. We summarise several pieces of work and highlight how they address the challenges above, and also hint at future research directions.
Keywords: Multi-robot systems, decision-making under uncertainty, Markov models, formal methods, asynchronous execution
DOI: 10.3233/AIC-220118
Journal: AI Communications, vol. 35, no. 4, pp. 433-441, 2022
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