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Simple Reinforcement Learning Framework

License: Apache License 2.0

Python 100.00%
reinforcement-learning machine-learning neural-network ddpg trpo evolution-strategies rainbow deep-reinforcement-learning asynchronous-advantage-actor-critic

srlf's Introduction

SRLF

Simple Reinforcement Learning Framework


SRLF helps to set up and train agent using one of these five algorithms:

  1. Evolution strategies (paper)
  2. Deep Deterministic Policy Gradient (paper)
  3. TRPO (paper)
  4. Rainbow (paper)
  5. A3C (paper)

I didn't make very user-friendly interface, but if you know how the algorigthm you want to use works, you can do it more or less easily.

To use, follow these steps:

  1. Choose algorithm you want to use
  2. Be sure you know how it works
  3. Study this implementation and how hyperparameters are used
  4. Use prepare_config.py as an example to make your config. Also check helpers/utils.py to know how to set some of non-obvious hyperparameters (like trainer)
  5. Launch python3 prepare_config.py to make config-file
  6. Launch python3 run_experiment.py to run experiment (you should also check how run_experiment.py works)
  7. Enjoy!

I also hope that framework can be helpful for people who want to study how to implement some of 5 algorithms that can be found here.

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