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Reinforcement Learning


Reinforcement Learning Books

Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more
Reinforcement Learning: Industrial Applications of Intelligent Agents
Algorithms for Reinforcement Learning
Deep Reinforcement Learning in Action
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Bandit Algorithms
 
by
Tor Lattimore
Decision Making Under Uncertainty: Theory and Application (MIT Lincoln Laboratory Series)
Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3)
Markov Decision Processes: Discrete Stochastic Dynamic Programming (Wiley Series in Probability and Statistics)
Algorithms for Decision Making
Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more
Bandit Algorithms for Website Optimization: Developing, Deploying, and Debugging
The Capital Function
Reinforcement Learning from Human Feedback: LLM alignment and post-training
Build a Robo-Advisor with Python (From Scratch): Automate your financial and investment decisions
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Lists

Reinforcement Learning by Richard S. SuttonMarkov Decision Processes by Martin L. PutermanAlgorithms for Reinforcement Learning by Csaba SzepesvariConvex Optimization by Stephen BoydAlgorithms for Reinforcement Learning by Csaba Szepesvari
Reinforcement Learning
18 books — 3 voters