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MARC Seminar Series 04
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Multi-Agent Path Finding and Its Applications
Time: October 24, 2025, 14:30-15:30 (CET).
Location: Hybrid. Room: U2-020 Ypsilon, Mälardalen University, Västerås Campus
Seminar Abstract
The coordination of robots and other agents is becoming increasingly important for industry. For example, on the order of one thousand robots already navigate autonomously in Amazon fulfillment centers to move inventory pods all the way from their storage locations to the picking stations that need the products they store (and vice versa). Optimal and, in some cases, even approximately optimal path planning for these robots is NP-hard, yet one must find high-quality collision-free paths for them in real-time. Algorithms for such multi-agent path-finding problems have been studied in robotics and theoretical computer science for a long time, but are insufficient since they are either fast but produce insufficient solution quality or produce good solution quality but are too slow. In this talk, Prof.Koenig will discuss different variants of multi-agent path-finding problems, innovative solutions to them, and their applications. He will also discuss how a team of Ph.D. students from his research group and a collaborating research group from Monash University used multi-agent path-finding technology to win the NeurIPS-20 Flatland train scheduling competition. Both NSF and Amazon Robotics have funded our research on this topic.
Speaker
Sven Koenig is the Professor at the University of California, Irvine
Sven Koenig is Chancellor's Professor and Bren Chair at the University of California, Irvine. Most of his research centers around techniques for decision making (planning and learning) that enable single situated agents (such as robots or decision-support systems) and teams of agents to act intelligently in their environments and exhibit goal-directed behavior in real-time, even if they have only incomplete knowledge of their environment, imperfect abilities to manipulate it, limited or noisy perception or insufficient reasoning speed.
Additional information about him can be found on his webpage: idm-lab.org