Overview of Multi-Agent Reinforcement Learning: Principles, Algorithms, and Challenges
1. Introduction Multi-Agent Reinforcement Learning (MARL) is an important branch of reinforcement learning that extends the traditional single-agent reinforcement learning concept to multi-agent environments. In MARL, multiple agents learn optimal strategies through interactions with the environment and other agents to maximize cumulative rewards in cooperative or competitive scenarios. Adversarial interactions among agents in MAgent (mixed … Read more