How to train Multi Agent Collaborative Agents with Reinforcement Learning (CTDE Explained)

In this video, we train Multi-agent Navigation AI agents to collaborate in complex obstacle courses. We learned the basics of creating custom Reinforcement Learning environments, how to design observation spaces, action spaces, and reward spaces, as well as the basics of LCS (local coordinate systems) in agentic systems. We then talk about Actor Critic methods like A2C and PPO, and how to train agents using them. We discuss two multi-agent RL algorithms, namely Independent PPO (I-PPO) and the more advanced Multi Agent PPO (MA-PPO). MA-PPO is inspired by MA-DDPG, which is a Centralized Trainin…