iq-scm / tensorflow-reinforce

Implementations of Reinforcement Learning Models in Tensorflow

Tensorflow-Reinforce

A collection of Tensorflow implementations of reinforcement learning models. Models are evaluated in OpenAI Gym environments. Any contribution/feedback is more than welcome. Disclaimer: These implementations are used for educational purposes only (i.e., to learn deep RL myself). There is no guarantee that the exact models will work on any of your particular RL problems without changes.

Environments

This codebase works in both Python 2.7 and 3.5. The models are implemented in Tensorflow 1.0.

Models

Model	Code	References
Cross-Entropy Method	run_cem_cartpole	Cross-entropy method
Tabular Q Learning	rl/tabular_q_learner	Sutton and Barto, Chapter 8
Deep Q Network	rl/neural_q_learner	Mnih et al.
Double Deep Q Network	rl/neural_q_learner	van Hasselt et al.
REINFORCE Policy Gradient	rl/pg_reinforce	Sutton et al.
Actor-critic Policy Gradient	rl/pg_actor_critic	Minh et al.
Deep Deterministic Policy Gradient	rl/pg_ddpg	Lillicrap et al.

License

MIT