The Open Ant: A Robot Platform for Reinforcement Learning Research
The Open Ant is presented: a physical variant of the commonly used Gymnasium Ant environment, along with a simulation, that demonstrates that competent walking policies can be learned from scratch in approximately one hour directly from the physical robot's experience for two substantially different RL algorithms: SARSA($\lambda$) and Soft Actor-Critic (SAC).