Hands-On Neuroevolution with Python

Dive into 'Hands-On Neuroevolution with Python' to understand how to apply evolutionary algorithms to enhance artificial neural network design. Using Python, you'll explore practical examples in robotics, gaming, and simulation, equipping yourself with actionable skills to tackle neural network optimization.

What this Book will help me do

• Master the implementation of neuroevolution algorithms including NEAT, HyperNEAT, and others using Python.
• Gain experience solving real-world problems with reinforcement learning and evolutionary strategies.
• Optimize neural network performance by applying neuroevolution to their architecture and training methods.
• Develop agents capable of tasks like autonomous navigation and playing complex video games.
• Analyze algorithm effectiveness with advanced techniques such as visualization and performance metrics.

Author(s)

None Omelianenko brings deep expertise in artificial intelligence and applied neuroevolution methods. With a strong background in programming and AI-based problem solving, they share a practical and engaging approach to implementing complex algorithms. This book reflects their dedication to making advanced techniques approachable for learners.

Who is it for?

If you're a machine learning enthusiast or AI researcher wanting to implement neuroevolution strategies, this book is for you. Ideal for practitioners with a basic grasp of Python and neural networks, it helps you advance your projects by mastering these unique algorithms. It's perfect for those aiming to innovate in neural network optimization.