دانلود کتاب Fundamentals of Reinforcement Learning

Preface
Acknowledgments
Contents
About the Author
Abbreviations
Chapter 1: Introduction
1.1 Artificial Intelligence
1.2 Machine Learning
1.3 Reinforcement Learning
1.4 History
References
Chapter 2: Concepts
2.1 Markov Chain
2.2 Markov Decision Process
2.3 Bellman Equation
2.4 Algorithm Approaches
References
Chapter 3: Q-Learning Algorithm
3.1 Operation of the Algorithm
3.2 Construction of the Q-Table
References
Chapter 4: Development Tools
4.1 OpenAI Gym
4.2 TF-Agents
4.3 Reinforcement Learning Toolbox
4.4 Keras
4.5 Data Sources
References
Chapter 5: Practice with Code
5.1 Getting to Know the Environment
5.2 Taking Random Actions
5.3 Training with the Algorithm
5.4 Testing the Q-Table
5.5 Testing the Trained Agent
References
Chapter 6: Recent Applications and Future Research
6.1 Artificial General Intelligence
6.2 Board Games
6.3 Digital Games
6.4 Robotics
6.5 Education
6.6 Quantum Mechanics
6.7 Mathematics
References
Index