Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python

Abhishek Nandy, Manisha Biswas



Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. You’ll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. 
Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markov’s Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI  before looking at Open AI Gym. You’ll then learn about Swarm Intelligence with Python in terms of reinforcement learning.
The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. There’s also coverage of Keras, a framework that can be used with reinforcement learning. Finally, you'll delve into Google’s Deep Mind and see scenarios where reinforcement learning can be used. 
What You'll Learn 
  • Absorb the core concepts of the reinforcement learning process
  • Use advanced topics of deep learning and AI
  • Work with Open AI Gym, Open AI, and Python 
  • Harness reinforcement learning with TensorFlow and Keras using Python
Who This Book Is For
Data scientists, machine learning and deep learning professionals, developers who want to adapt and learn reinforcement learning.



《強化學習》討論了強化學習中重要的算法實現,包括馬爾可夫決策過程和半馬爾可夫決策過程。下一部分將向您展示如何開始使用Open AI,然後介紹Open AI Gym。接著,您將學習使用Python進行強化學習的群體智能。

本書的最後一部分從TensorFlow環境開始,概述了如何將強化學習應用於TensorFlow。還介紹了可以與強化學習一起使用的框架Keras。最後,您將深入研究Google的Deep Mind,並了解強化學習可以應用的場景。

- 掌握強化學習過程的核心概念
- 使用深度學習和人工智慧的高級主題
- 使用Open AI Gym、Open AI和Python進行工作
- 使用Python、TensorFlow和Keras進行強化學習

- 數據科學家、機器學習和深度學習專業人士
- 希望適應和學習強化學習的開發人員