Research Post
Two popular optimal search-based solvers for the multi-agent pathfinding (MAPF) problem, Conflict-Based Search (CBS) and Increasing Cost Tree Search (ICTS), have been extended separately for continuous time domains and symmetry breaking. However, an approach to symmetry breaking in continuous time domains remained elusive. In this work, we introduce a new algorithm, Conflict-Based Increasing Cost Search (CBICS), which is capable of symmetry breaking in continuous time domains by combining the strengths of CBS and ICTS. Our experiments show that CBICS often finds solutions faster than CBS and ICTS in both unit time and continuous time domains.
Feb 15th 2022
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chair Adam White: Learning Expected Emphatic Traces for Deep RL
Jun 28th 2021
Research Post
Jun 2nd 2021
Research Post
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