Statistical Reinforcement Learning : Modern Machine Learning Approaches

Sugiyama, Masashi

Statistical Reinforcement Learning : Modern Machine Learning Approaches - New York CRC Press 2024 - xiv, 192p. 23 x 15 cm

I. Introduction

1. Introduction to Reinforcement Learning

II. Model-Free Policy Iteration

2. Policy Iteration with Value Function Approximation

3. Basis Design for Value Function Approximation

4. Sample Reuse in Policy Iteration

5. Active Learning in Policy Iteration

6. Robust Policy Iteration

III. Model-Free Policy Search

7. Direct Policy Search by Gradient Ascent

8. Direct Policy Search by Expectation-Maximization

9. Policy-Prior Search

IV. Model-Based Reinforcement Learning

10. Transition Model Estimation

Dimensionality Reduction for Transition Model Estimation

9781032708119

006.31 / SUG

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