Formalizes CT-TAPF problem and introduces CT-TCBS optimal solver using incremental expansion for team formation plus task-centric sub-optimal solvers that improve efficiency over agent-centric baselines.
Proceedings of the AAAI Conference on Artificial Intelligence , author=
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UNVERDICTED 3representative citing papers
DiffLNS uses a discrete diffusion initializer to produce warm-start plans that lift LNS2 success rates to 95.8% across 20 congested MAPF settings, generalizing from 96 to 312 agents.
Distance-r Independent Unlabeled Multi-Agent Pathfinding is PSPACE-complete, with reduction-based and configuration-generator algorithms that solve instances with hundreds of agents.
citing papers explorer
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Multi-Agent Cooperative Transportation: Optimal and Efficient Task Allocation and Path Finding
Formalizes CT-TAPF problem and introduces CT-TCBS optimal solver using incremental expansion for team formation plus task-centric sub-optimal solvers that improve efficiency over agent-centric baselines.
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Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention
DiffLNS uses a discrete diffusion initializer to produce warm-start plans that lift LNS2 success rates to 95.8% across 20 congested MAPF settings, generalizing from 96 to 312 agents.
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Distance-Constrained Unlabeled Multi-Agent Pathfinding
Distance-r Independent Unlabeled Multi-Agent Pathfinding is PSPACE-complete, with reduction-based and configuration-generator algorithms that solve instances with hundreds of agents.