Reinforcement Learning - An Introduction
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Chapter 14: Psychology
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Reinforcement Learning: An Introduction book
Part I: Tabular Solution Methods
Chapter 2: Multi-armed Bandits
Chapter 3: Finite Markov Decision Processes
Chapter 4: Dynamic Programming
Chapter 5: Monte Carlo Methods
Chapter 6: Temporal-Difference Learning
Chapter 7: n-step Bootstrapping
Chapter 8: Planning and Learning with Tabular Methods
Part II: Approximate Solution Methods
Chapter 9: On-policy Prediction with Approximation
Chapter 10: On-policy Control with Approximation
Chapter 12: Eligibility Traces
Chapter 13: Policy Gradient Methods
Part III: Looking Deeper
Chapter 14: Psychology
Appendix
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