Deep Reinforcement Learning: Frontiers of Artificial Intelligence
Authors: Mohit Sewak
ISBN-10: 9811382840
ISBN-13: 9789811382840
Edition 版次: 1st ed. 2019
Publication Date 出版日期: 2019-07-02
Print Length 页数: 203 pages
Book Description
By finelybook
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications,and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems,and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms,but also prepares them to implement systems such as those created by Google Deep Mind in actual code.
This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
1. Introduction to Reinforcement Learning
2. Mathematical and Algorithmic Understanding of Reinforcement Learning
3. Coding the Environment and MDP Solution
4. Temporal Difference Learning,SARSA,and Q-Learning
5.Q-Learning in Code
6. Introduction to Deep Learning
7. Implementation Resources
8. Deep QNetwork(DQN),Double DQN,and Dueling DQN
9. Double DQN in Code
10. Policy-Based Reinforcement Learning Approaches
11. Actor-Critic Models and the A3C
12.A3C in Code
13. Deterministic Policy Gradient and the DDPG
14. DDPG in Code
