HULK introduces a hierarchical online coordination method for large multi-agent teams executing continual uncertain temporal logic tasks by interleaving subteam assignment and local dynamic execution.
An overview of vehicle routing problems
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ARMATA is a new end-to-end autoregressive model with multi-stage decoding that unifies allocation and routing for multi-agent systems and reports up to 20% better solutions than OR-Tools, CPLEX, and LKH-3 in seconds instead of hours.
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HULK: Large-scale Hierarchical Coordination under Continual and Uncertain Temporal Tasks
HULK introduces a hierarchical online coordination method for large multi-agent teams executing continual uncertain temporal logic tasks by interleaving subteam assignment and local dynamic execution.
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ARMATA: Auto-Regressive Multi-Agent Task Assignment
ARMATA is a new end-to-end autoregressive model with multi-stage decoding that unifies allocation and routing for multi-agent systems and reports up to 20% better solutions than OR-Tools, CPLEX, and LKH-3 in seconds instead of hours.