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Found 2 papers, 1 papers with code
HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding
With a simple training scheme and implementation, HiMAP demonstrates competitive results in terms of success rate and scalability in the field of imitation-learning-only MAPF, showing the potential of imitation-learning-only MAPF equipped with inference techniques.
LPMARL: Linear Programming based Implicit Task Assigment for Hiearchical Multi-Agent Reinforcement Learning
Earlier studies have tried to resolve this issue by using hierarchical MARL to decompose the main task into subproblems or employing an intrinsic reward to induce interactions for learning an effective policy.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
