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DQN

Modular implementation of DQN algorithm.

Dependencies

Features

  • Using a neural network based as the function approximator for Q-learning
  • Using a target network and soft-update to synchronoze target network with Q-network
  • Using gradient clipping to make small but consistent updates towards optimal Q-network

Bonus

Usage

To train a model for Cartpole-v0:

$ python test_graph_dqn.py 

To view the tensorboard

$tensorboard --logdir .

Results

  • Tensorboard Progress Bar

About

A short tutorial about tips and tricks used in implementation of Deep Q-networks that helped in creating a first AI that can successfully play Atari.

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