Omelianenko Hands-On Neuroevolution with Python

Build high-performing artificial neural network architectures using neuroevolution-based algorithms
1. Auflage 2019
ISBN: 978-1-83882-200-2
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 368 Seiten

No detailed description available for "Hands-On Neuroevolution with Python".

Autoren/Hrsg.

Omelianenko, Iaroslav

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik

Inhaltsverzeichnis

Table of Contents - Overview of Neuroevolution Methods
- Python Libraries and Environment Setup
- Using NEAT for XOR Solver Optimization
- Pole-Balancing Experiments
- Autonomous Maze Navigation
- Novelty Search Optimization Method
- Hypercube-Based NEAT for Visual Discrimination
- ES-HyperNEAT and the Retina Problem
- Co-Evolution and the SAFE Method
- Deep Neuroevolution
- Best Practices, Tips, and Tricks
- Concluding Remarks

Über Autor(innen)

Omelianenko Iaroslav:

Iaroslav Omelianenko occupied the position of CTO and research director for more than a decade. He is an active member of the research community and has published several research papers at arXiv, ResearchGate, Preprints, and more. He started working with applied machine learning by developing autonomous agents for mobile games more than a decade ago. For the last 5 years, he has actively participated in research related to applying deep machine learning methods for authentication, personal traits recognition, cooperative robotics, synthetic intelligence, and more. He is an active software developer and creates open source neuroevolution algorithm implementations in the Go language.