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Reinforcement Learning
A Unified View on Planning and Learning
A Unified View on Reinforcement Learning Approaches
Backups in Reinforcement Learning
Dynamic Programming for Reinforcement Learning
Eligibility Traces
Importance Sampling
Markov Processes in Machine Learning
Monte Carlo Methods in Reinforcement Learning
N-step Bootstrapping
Temporal Difference Learning
The Exploitation-Exploration Trade-Off
The Setting for Reinforcement Learning
Decision Time Planning
Function Approximation in Reinforcement Learning
Off Policy Prediction and Control with Approximation
On Policy Prediction and Control with Approximation
Policy Gradient Methods
The Library
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Reinforcement Learning - An Introduction by Sutton and Barto