MARL-Papers

Why we included this project

This is the kind of reading list you keep coming back to once you start working in multi-agent reinforcement learning. Instead of a flat pile of links, it sorts hundreds of papers by research thread, with sections for joint action learning, cooperation and competition, coordination, security, self-play, and learning to communicate. That organization helps because the field spans game theory, robotics, and increasingly large language models, and the list tracks those newer application areas alongside the established classics. It also opens with tutorials and review papers, which saves time when you need a map before digging into primary sources. Since the maintainers accept pull requests, the collection stays current as the community adds to it, making it a practical base for a thesis reading list or a seminar syllabus.