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All Projects → rllab-snu → Deep-Reinforcement-Learning

rllab-snu / Deep-Reinforcement-Learning

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Introduction to Deep Reinforcement Learning

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Jupyter Notebook
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Deep-Reinforcement-Learning

This repository provides implementations of deep reinforcement learning algorithms. The codes are mainly written in python3 using Ipython Notebook.

Chapter 01: Behavior Cloning (Supervised Learning)

Chapter 02: Value Iteration and Policy Iteration

Chapter 03: SARSA and Q Learning

Chapter 04: Deep Q Learning

Chapter 05: Policy Gradient

Chapter 06: Actor Critic Methods

Chapter 07: Model based RL and Learning from Demonstrations

Chapter 08: Inverse Reinforcement Learning

Doker files for environment settings

https://github.com/SKYnSPACE/DockerFiles/tree/master/py3-gym-tf1.6

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