Pole Balancing
Neural networks evolve to balance a pole on a moving cart by applying force in either direction.
Generation0
Best Fitness0
Alive Count0
About This Simulation
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.
Technical Details
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°