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RLkit: A simple Reinforcement Learning library

This project is still a work in progress. More algorithms and detailed documentation coming soon :)

Currently supported agents-

  1. Random agent
  2. REINFORCE (Policy Gradients)
  3. DQN
  4. DQN with baseline
  5. Actor-Critic

See examples for details on how to use the library.

Requirements-

tensorflow==1.11.0
gym==0.10.8
numpy==1.15.4

New in v0.2

  • Added DQN and DQN with baseline agents
  • Added ActorCritic agent
  • Added support for various activation functions

Upcoming

  • Duelling DQN
  • Support for logging and plotting
  • Support for adding seeds
  • Support for custom environments

Release files for RLkit 0.2.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for RLkit 0.2.0
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Release files / RLkit-0.2.0.tar.gz

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