Reinforcement Learning for sumo robots using SAC, PPO, A2C algorithms

Hi everyone,

I’ve recently finished the first version of RobotSumo-RL, an environment specifically designed for training autonomous combat agents. I wanted to create something more dynamic than standard control tasks, focusing on agent-vs-agent strategy.

Key features of the repo:

– Algorithms: Comparative study of SAC, PPO, and A2C using PyTorch.

– Training: Competitive self-play mechanism (agents fight their past versions).

– Physics: Custom SAT-based collision detection and non-linear dynamics.

– Evaluation: Automated ELO-based tournament system.

Link: https://github.com/sebastianbrzustowicz/RobotSumo-RL

I’m looking for any feedback.