AI Agent
Watch as our AI agent learns to balance and guide the ball using Deep Q-Learning. The agent processes 16 different state variables to make intelligent decisions about platform movement and rotation.
Training Controls
- Start/Stop training using the control panel
- Adjust learning parameters in real-time
- Monitor training progress and metrics
Objectives
- Guide the ball into the basket
- Maintain stability and control
- Optimize movement efficiency
Neural Network
16 Inputs
State Variables
Actions
27 Possible
Movement Combinations
Max Reward
100 Points
Per Successful Episode
Learning Rate
Adaptive
Dynamic Optimization