University of Alberta Campus (CSC-333)
Presenter: Thayne Walker, PostDoc w. Nathan Sturtevant
Title: Multi-Agent Pathfinding in Discrete-Continuous Time and Space
Abstract: In the multi-agent pathfinding (MAPF) problem, agents must move from their current locations to their individual destinations while avoiding collisions. MAPF has many real-world applications such as navigation, warehouse automation, package delivery and games. Ideally, agents move to their destinations as quickly and efficiently as possible, however, it is computationally expensive to find optimized mutually conflict-free paths for multiple agents – especially as the number of agents increases. In this talk, we extend MAPF beyond traditional toy problems on unit-cost planar graphs to real-world inspired settings, where agent's actions are coordinated on arbitrary planning graphs with actions of variable duration. This talk covers several algorithms: E-ICTS, CCBS and CBICS as well as important techniques related to continuous-time MAPF such as conflict avoidance and symmetry breaking.
Bio: Thayne Walker researches the topic of Multi-Agent Pathfinding with non-unit costs for movement, which can be used to model real-world problems with agents that have complex movement constraints. He completed his PhD from the University of Denver in 2022 and is currently a PostDoc working with Nathan Sturtevant. He is also a researcher at the Lockheed Martin AI Center.
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