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Reinforcement Learning With Open AI, TensorFlow and Keras Using Python 无水印原版pdf.pdf

发布时间：2022-06-15 发布人：admin 分类：说明书 资料大小：11.02M 资料格式：pdf 举报 版权申诉
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    Cover
    Copyright
    Contents
    About the Authors
    Introduction
    1: Reinforcement Learning Basics
    What Is Reinforcement Learning?
    Faces of Reinforcement Learning
    The Flow of Reinforcement Learning
    Different Terms in Reinforcement Learning
    Gamma
    Lambda
    Interactions with Reinforcement Learning
    RL Characteristics
    How Reward Works
    Agents
    RL Environments
    Deterministic
    DFA (Deterministic Finite Automata)
    NDFA (Nondeterministic Finite Automaton)
    Observable
    Discrete or Continuous
    Single Agent and Multiagent Environments
    Conclusion
    2: RL Theory and Algorithms
    Theoretical Basis of Reinforcement Learning
    Where Reinforcement Learning Is Used
    Manufacturing
    Inventory Management
    Delivery Management
    Finance Sector
    Why Is Reinforcement Learning Difficult?
    Preparing the Machine
    Installing Docker
    An Example of Reinforcement Learning with Python
    What Are Hyperparameters?
    Writing the Code
    What Is MDP?
    The Markov Property
    The Markov Chain
    MDPs
    SARSA
    Temporal Difference Learning
    How SARSA Works
    Q Learning
    What Is Q?
    How to Use Q
    SARSA Implementation in Python
    The Entire Reinforcement Logic in Python
    Dynamic Programming in Reinforcement Learning
    Conclusion
    3: OpenAI Basics
    Getting to Know OpenAI
    Installing OpenAI Gym and OpenAI Universe
    Working with OpenAI Gym and OpenAI
    More Simulations
    OpenAI Universe
    Conclusion
    4: Applying Python to Reinforcement Learning
    Q Learning with Python
    The Maze Environment Python File
    The RL_Brain Python File
    Updating the Function
    Using the MDP Toolbox in Python
    Understanding Swarm Intelligence
    Applications of Swarm Intelligence
    Ant-Based Routing
    Crowd Simulations
    Human Swarming
    Swarm Grammars
    Swarmic Art
    The Rastrigin Function
    Swarm Intelligence in Python
    Building a Game AI
    The Entire TFLearn Code
    Conclusion
    5: Reinforcement Learning with Keras, TensorFlow, and ChainerRL
    What Is Keras?
    Using Keras for Reinforcement Learning
    Using ChainerRL
    Installing ChainerRL
    Pipeline for Using ChainerRL
    Deep Q Learning: Using Keras and TensorFlow
    Installing Keras-rl
    Training with Keras-rl
    Conclusion
    6: Google's DeepMind and the Future of Reinforcement Learning
    Google DeepMind
    Google AlphaGo
    What Is AlphaGo?
    Monte Carlo Search
    Man vs. Machines
    Positive Aspects of AI
    Negative Aspects of AI
    Conclusion
    Index
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