Habib Hands-On Q-Learning with Python

Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
1. Auflage 2019
ISBN: 978-1-78934-575-9
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 212 Seiten

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

Autoren/Hrsg.

Habib, Nazia

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - Brushing Up on Reinforcement Learning Concepts
- Getting Started with the Q-Learning Algorithm
- Setting Up Your First Environment with OpenAI Gym
- Teaching a Smartcab to Drive Using Q-Learning
- Building Q-Networks with TensorFlow
- Digging Deeper into Deep Q-Networks with Keras and TensorFlow
- Decoupling Exploration and Exploitation in Multi-Armed Bandits
- Further Q-Learning Research and Future Projects
- Assessments

Über Autor(innen)

Habib Nazia:

Nazia Habib is a data scientist who has worked in a variety of industries to generate predictive analytics solutions for diverse groups of stakeholders. She is an expert in building solutions to optimization problems under conditions of uncertainty. Her projects range from predicting user behavior and engagement with social media apps to designing adaptive testing software. Her ongoing specialization is in designing custom reinforcement learning algorithms for modeling control problems with limited inputs that converge to optimal solutions.