README.md

DRL-Books-resources

This repo provides some Deep Reinforcement Learning (DRL) Books and Links for Studying.

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Reinforcement Learning (RL)

• Reinforcement Learning (RL) is a Semi-supervised machine-learning approach.

• It is concerned with learning control laws and policies to interact with a complex environment from experience

• The RL agent goes through many trial and error steps to maximize the reward it gets from the environment

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Deep Reinforcement Learning (DRL)

• In recent years, A combination of deep learning and RL Classic RL is proposed as Deep Reinforcement Learning (DRL)

• In 2015, Google DeepMind introduced deep Qnetwork (DQN) delivering results exceeding humans in playing Atari games.

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Online Courses

• Stanford CS234: Reinforcement Learning | Winter 2019

• DeepMind x UCL | RL Course by David Silver

• UC Berkeley CS 285: Deep Reinforcement Learning Fall 2022

• Reinforcement Learning by Steve Brunton

• Advanced AI Deep Reinforcement Learning in Python

• Reinforcement Learning using python | sentdex

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Books

1. Sutton, Richard S., and Andrew G. Barto. Reinforcement learning: An introduction. MIT press, 2018.‏

2. Brunton, Steven L., and J. Nathan Kutz. Data-driven science and engineering: Machine learning, dynamical systems, and control, ch 11, Cambridge University Press, 2022.‏

3. Gym, O., and Nimish Sanghi. Deep reinforcement learning with python. Apress, 2021.‏ his code repo here

4. simple presentation that I made