Rafal Niedziólka-Domanski

A Case for Decentralized Model-Based Multi-agent Reinforcement Learning

Experimental results demonstrate that model-based, decentralized approach can serve as an effective alternative to centralized training for cooperative multi-agent reinforcement learning and indicate that model-based, decentralized approach can serve as an effective alternative to centralized training for cooperative multi-agent reinforcement learning.