Comprehensive visualization of neural network evolution across generations
Shows how neural network weights changed across generations. Darker areas indicate stable connections, while bright areas show active learning.
Individual analysis of each neural network layer, revealing which parts of the brain adapted most during training.
Timeline view showing when major neural adaptations occurred, highlighting critical learning moments.
Timeline view showing when major neural adaptations occurred, highlighting critical learning moments.
Radar chart showing how the AI's decision-making patterns evolved across different driving scenarios.
Timeline of behavioral changes, showing when the AI learned specific driving behaviors like cornering and speed control.
Side-by-side comparison of driving behaviors between early chaotic generations and later optimized ones.
Analysis of how different mutation rates affected learning speed and final performance.
Which sensors the AI learned to prioritize for different driving situations and track sections.
Analysis of sensor overlap and which inputs provide unique vs redundant information for driving decisions.
Analysis of sensor overlap and which inputs provide unique vs redundant information for driving decisions.
Overlay of racing lines from different generations, showing the evolution from chaotic paths to optimized racing lines.
Heatmap showing the most frequently used racing lines, revealing the AI's preferred paths through the track.
Speed and steering intensity overlaid on the racing line, showing where the AI brakes, accelerates, and turns.
Watch the project demonstration showcasing the AI car's training and racing capabilities in action.
Interactive visualization of the neural network structure and activation patterns during training.