Title Statements
- Full title :Reinforcement Learning / D., Phil Winder Ph.
Edition Statements
- Publication Date:2020.
Publication Statements
- Publisher(s):O'Reilly Media, Inc
- Place of Publication:S.l
- Language:und
- Publication Date:2020.
Notes
Title from content provider.
The Physical Object
- Description:1 online resource
Edition Identifiers
- ISBN:9781098114831, 1098114833
- oclc:on1228538063
Table of Contents
Intro -- Copyright -- Table of Contents -- Preface -- Objective -- Who Should Read This Book? -- Guiding Principles and Style -- Prerequisites -- Scope and Outline -- Supplementary Materials -- Conventions Used in This Book -- Acronyms -- Mathematical Notation -- Fair Use Policy -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Why Reinforcement Learning? -- Why Now? -- Machine Learning -- Reinforcement Learning -- When Should You Use RL? -- RL Applications -- Taxonomy of RL Approaches -- Model-Free or Model-Based -- How Agents Use and Update Their Strategy
Discrete or Continuous Actions -- Optimization Methods -- Policy Evaluation and Improvement -- Fundamental Concepts in Reinforcement Learning -- The First RL Algorithm -- Is RL the Same as ML? -- Reward and Feedback -- Reinforcement Learning as a Discipline -- Summary -- Further Reading -- Chapter 2. Markov Decision Processes, Dynamic Programming, and Monte Carlo Methods -- Multi-Arm Bandit Testing -- Reward Engineering -- Policy Evaluation: The Value Function -- Policy Improvement: Choosing the Best Action -- Simulating the Environment -- Running the Experiment
Speedy Q-Learning -- Accumulatin…
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