Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Only a subset of these MARL algorithms both do not require agent...
Multi-agent reinforcement learning (MARL) is an emerging area of research. However, it lacks two important elements: a coherent view on MARL, and a well-defined problem objective. ...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...
Abstract. In multi-agent reinforcement learning systems, it is important to share a reward among all agents. We focus on the Rationality Theorem of Profit Sharing [5] and analyze ...