Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...
—Recently, game theory has been proposed as a tool for cooperative control. Specifically, the interactions of a multiagent distributed system are modeled as a non-cooperative ga...
This paper presents a role-based agent teamwork language called RoB-MALLET (Role-Based Multi-Agent Logic Language for Encoding Teamwork). Roles have been used to form multi-agent t...
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...