{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T14:40:11Z","timestamp":1777560011980,"version":"3.51.4"},"reference-count":35,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIC"],"published-print":{"date-parts":[[2022,9,20]]},"abstract":"<jats:p>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)\u00a0temporal uncertainty, in particular of action execution; (ii)\u00a0the ability to provide rich guarantees of performance, both at a local (robot) level and at a global (team) level; and (iii)\u00a0scaling 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.<\/jats:p>","DOI":"10.3233\/aic-220118","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T11:21:38Z","timestamp":1662117698000},"page":"433-441","source":"Crossref","is-referenced-by-count":2,"title":["Decision-making under uncertainty for multi-robot systems"],"prefix":"10.1177","volume":"35","author":[{"given":"Bruno","family":"Lacerda","sequence":"first","affiliation":[{"name":"Oxford Robotics Institute, University of Oxford, United Kingdom"}]},{"given":"Anna","family":"Gautier","sequence":"additional","affiliation":[{"name":"Oxford Robotics Institute, University of Oxford, United Kingdom"}]},{"given":"Alex","family":"Rutherford","sequence":"additional","affiliation":[{"name":"Oxford Robotics Institute, University of Oxford, United 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