AI Cat Learning to Run

A developer creates AI agents that learn to walk using neural networks and evolutionary algorithms. The project simulates cat-like creatures with virtual muscles and joints, using Box2D physics engine for stability. Through iterative training with 1,000 agents running in parallel across 14 CPU cores, the AI gradually develops from basic movement to smooth walking gaits. The training process shows how agents evolve from struggling with joint coordination to achieving efficient locomotion patterns over 240+ iterations.