This simulation demonstrates the NEAT algorithm applied to the classic pole balancing problem. Neural networks evolve to balance a pole on a moving cart by applying force in either direction.
Neural Network Inputs: Cart position and pole angle
Neural Network Outputs: Force direction (push left or right)
Fitness Function: Based on time the pole remains balanced
Failure Conditions: Cart moves too far (±2.4m) or pole angle exceeds ±12°