Book Content
chapters • 12h16m total length
1. Overview of Neuroevolution Methods
2. Python Libraries and Environment Setup
3. Using NEAT for XOR Solver Optimization
4. Pole-Balancing Experiments
5. Autonomous Maze Navigation
6. Novelty Search Optimization Method
7. Hypercube-Based NEAT for Visual Discrimination
8. ES-HyperNEAT and the Retina Problem
9. Co-Evolution and the SAFE Method
10. Deep Neuroevolution
11. Best Practices, Tips, and Tricks
12. Concluding Remarks
