Deep Reinforcement Learning

This page contains a list of the papers about the deep reinforcement learning, organized in sections by subject.

Books & Courses

1. Reinforcement Learning: An Introduction, by Richard S. Sutton and Andrew G. Barto, 2018

2. UCL Course on reinforcement learning, by David Silver, 2015

3. UC Berkeley Course on deep reinforcement learning, by Sergey Levine, 2018

4. Deep reinforcement learning Course with Tensorflow, by Thomas Simonini

5. Deep Learning, by Hung-yi Lee

6. Machine Learning and Python, by huaxiaozhuan

Web Blog

1. Implementation of Reinforcement Learning Algorithms

2. Deep Q Network vs Policy Gradients, by Felix Yu, 2017

3. Deep Learning in a Nutshell: Reinforcement Learning

Multi-Armed Bandit

1. The Multi-Armed Bandit Problem and Its Solutions

Reinforcement Learning

1. Markov Decision Process

2. Model-based RL

3. Model-free RL: Monte Carlo Method

4. Model-free RL: Time Difference Learning

5. Value Function Approximation

6. Policy Gradients

7. Gym-1, Gym-2, Gym-3, Gym-4, Gym-5, Gym-6, Gym-7

DQN

Q-Learning but with a Deep Neural Network as a function approximator

1. Demystifying Deep Reinforcement Learning, by Tambet Matiisen, 2015

2. Human-level control through deep reinforcement learning, Nature, 2015

3. Torch implementation of Human-level control through deep reinforcement learning, by deepmind

4. Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning

5. learning-rate-for-deep-learning-neural-networks, by Jason Brownlee

Multi-Agent RL

1. Note-1, Note-2