Exploring Multi-Agent Reinforcement Learning: Techniques, Applications, and Future Directions

Abstract

Multi-Agent Reinforcement Learning (MARL) extends traditional reinforcement learning to environments with multiple interacting agents. This paper provides a comprehensive overview of MARL, covering its foundational principles, key algorithms, and real-world applications. We also discuss current challenges and potential future directions for research in this dynamic field.