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Implementation of selected reinforcement learning algorithms in Tensorflow. A3C, DDPG, REINFORCE, DQN, etc.

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Implementation of Reinforcement Learning Algorithms in Python

Implementation of selected reinforcement learning algorithms with tensorflow.

Implemented Algorithms

(Click into the links for more details)

Advanced
Policy Gradient Methods
Temporal Difference Learning
Monte Carlo Methods
Dynamic Programming MDP Solver

Environments

  • envs/gridworld.py: minimium gridworld implementation for testings

Dependencies

  • Python 2.7
  • Numpy
  • Tensorflow 0.12.1
  • OpenAI Gym (with Atari) 0.8.0
  • matplotlib (optional)

Tests

  • Files: test_*.py
  • Run unit test for [class]:

python test_[class].py

MIT License

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Implementation of selected reinforcement learning algorithms in Tensorflow. A3C, DDPG, REINFORCE, DQN, etc.

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