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.
The increasing cost tree search for optimal multi-agent pathfinding
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
C-ORCA* and C-ORCA*-MAPF proactively prevent deadlocks in continuous MAPF using entire trajectories and spatial dependencies, outperforming prior methods in solve rate, runtime, and flowtime.
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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Cooperative-ORCA*: Real-Time Proactive Deadlock Avoidance for Continuous-Space Multi-Agent Navigation
C-ORCA* and C-ORCA*-MAPF proactively prevent deadlocks in continuous MAPF using entire trajectories and spatial dependencies, outperforming prior methods in solve rate, runtime, and flowtime.