GA-Based Multi-Agent Reinforcement Learning for Playing Backgammon

摘要

The paper presents a genetic algorithm approach for evolving multi-agent reinforcement learning systems that are made up of a coalition of agents with bidding. The experiment results show the advantage of this approach over the single agent reinforcement learning approach, the pure GA approach and the reinforcement learning with bidding approach.