Interactive Multi-Agent Reinforcement Learning

This was a project with the IEEE NITK Computer Society. In this project, we developed and improved multi-agent reinforcement learning algorithms that enable interactive, collaborative, and negotiating behaviors in the mixed cooperative-competitive many-player games.

Link to project repository.