Synopses & Reviews
Synopsis
1: Introduction2: The Perceptron Model3: Artificial Neuron4: Neural Networks5: Theory on Learning6: Data Classification7: A Matrix Library8: Matrix-Based Neural Network9: Genetic Algorithm10: Genetic Algorithm in Action11: Traveling Salesman Problem12: Exiting a Maze13: Building Zoomorphic Creatures14: Evolving Zoomorphic Creature15: Neuroevolution16: Neuroevolution with NEAT17: The MiniMario Video GameLast Words (Afterword)
Synopsis
Cover classical algorithms commonly used as artificial intelligence techniques and program agile artificial intelligence applications using Pharo. This book takes a practical approach by presenting the implementation details to illustrate the numerous concepts it explains.
Along the way, you'll learn neural net fundamentals to set you up for practical examples such as the traveling salesman problem and cover genetic algorithms including a fun zoomorphic creature example. Furthermore,
Practical Agile AI with Pharo finishes with a data classification application and two game applications including a Pong-like game and a Flappy Bird-like game. This book is informative and fun, giving you source code to play along with. You'll be able to take this source code and apply it to your own projects.
What You Will Learn
- Use neurons, neural networks, learning theory, and more
- Work with genetic algorithms
- Incorporate neural network principles when working towards neuroevolution
- Include neural network fundamentals when building three Pharo-based applications
Who This Book Is ForCoders and data scientists who are experienced programmers and have at least some prior experience with AI or deep learning. They may be new to Pharo programming, but some prior experience with it would be helpful.