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cs.AI2025
Graph Attention-Guided Search for Dense Multi-Agent Pathfinding
Rishabh Jain, Keisuke Okumura, Michael Amir +1
Finding near-optimal solutions for dense multi-agent pathfinding (MAPF) problems in real-time remains challenging even for state-of-the-art planners. To this end, we develop a hybr…
cs.AI2025
The impact of behavioral diversity in multi-agent reinforcement learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
Many of the world's most pressing issues, such as climate change and global peace, require complex collective problem-solving skills. Recent studies indicate that diversity in indi…
cs.AI2024
CoDreamer: Communication-Based Decentralised World Models
Edan Toledo, Amanda Prorok
Sample efficiency is a critical challenge in reinforcement learning. Model-based RL has emerged as a solution, but its application has largely been confined to single-agent scenari…