🎾 Multi-Agent Proximal Policy Optimization approach to a competitive reinforcement learning problem

Capturing the Flag (CTF) Multi-Agent Reinforcement Learning (MARL) in CTF game environment. The project evaluates different approaches like Independent Q-Learning (IQL) and Multi-Agent Proximal Policy Optimization (MAPPO) for cooperative and competitive agent interactions in a grid-world environment.