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cs.AI2024
Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms
Michael Kölle, Yannick Erpelding, Fabian Ritz +3
Recent advances in Multi-Agent Reinforcement Learning have prompted the modeling of intricate interactions between agents in simulated environments. In particular, the predator-pre…
cs.AI2024
ClusterComm: Discrete Communication in Decentralized MARL using Internal Representation Clustering
Robert Müller, Hasan Turalic, Thomy Phan +3
In the realm of Multi-Agent Reinforcement Learning (MARL), prevailing approaches exhibit shortcomings in aligning with human learning, robustness, and scalability. Addressing this,…