Human-Level Control through Deep Reinforcement Learning

Tensorflow implementation of Human-level Control through Deep Reinforcement Learning

This implementation contains:

1. Deep Q-network and Q-learning
2. Experience replay memory
   • to reduce the correlations between consecutive updates
3. Network for Q-learning targets are fixed for intervals
   • to reduce the correlations between target and predicted Q-values

Agent attention from my MPhil project on deep reinforcement learning!

How the agent learnt to focus through time!

Requirements

• OpenAI gym
• Tensorflow
• Numpy
• Collections

and all of their dependencies.

References

• Code for Human-level control through deep reinforcement learning