In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
In this paper, we show how the dynamics of Q-learning can be visualized and analyzed from a perspective of Evolutionary Dynamics (ED). More specifically, we show how ED can be use...
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah