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What is in this repo?

Implementation of Reinforcement Learning algorithms in Python3 using he OpenAI framework and TensorFlow as neural network libraries. Results are shown with TensorBoard.

#Gym-A3C Implementation of the A3C algorithm for OpenAI Gym's Atari games. The implementation uses processes instead of threads to achieve real concurrency.

##How to run the A3C ? To launch the A3C with the default parameters, just use the following command. It is possible to see the available hyper parameters with the command -h.

python3.5 main.py Pong-v0

To see different plots like the rewards, the losses... it is necessary to launch TensorBoard with the command

tensorboard --logdir=tf_logs/

##Results

Pong-v0, 4 actors, 5 local steps and updating the network with an Adam Optimizer (learning rate: 1e-4).

#Useful papers A3C

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Implementation of a Reinforcement Learning algorithm for the game Slither.io using the Universe framework from openAI to emulate the game.

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