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cs.AI2026
Belief-Aware Multi-Agent Path Finding under Map Uncertainty
Viraj Parimi, Shao-Hung Chan, Han Zhang +2
Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static obstacles are known in advance…
cs.LG2026
MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning
Yusuf Syed, Viraj Parimi, Brian Williams
Temporally contrastive representation learning induces a latent structure capable of reducing long-horizon planning to inference in a low-dimensional linear system. However, existi…
cs.RO2026
Large Neighborhood Search for Multi-Agent Task Assignment and Path Finding with Precedence Constraints
Viraj Parimi, Brian C. Williams
Many multi-robot applications require tasks to be completed efficiently and in the correct order, so that downstream operations can proceed at the right time. Multi-agent path find…