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Algorithm and utilities for deep reinforcement learning

Project description

Rainy

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Reinforcement learning utilities and algrithm implementations using PyTorch.

API documentation

COMING SOON

Supported python version

Python >= 3.6.1

Implementation Status

Algorithm Multi Worker(Sync) Recurrent Discrete Action Continuous Action MPI support
DQN/Double DQN :heavy_check_mark: :x: :heavy_check_mark: :x: :x:
BootDQN/RPF :x: :x: :heavy_check_mark: :x: :x:
DDPG :heavy_check_mark: :x: :x: :heavy_check_mark: :x:
TD3 :heavy_check_mark: :x: :x: :heavy_check_mark: :x:
SAC :heavy_check_mark: :x: :x: :heavy_check_mark: :x:
PPO :heavy_check_mark: :heavy_check_mark: :heavy_check_mark: :heavy_check_mark: :heavy_check_mark:
A2C :heavy_check_mark: :small_red_triangle:(1) :heavy_check_mark: :heavy_check_mark: :x:
ACKTR :heavy_check_mark: :x:(2) :heavy_check_mark: :heavy_check_mark: :x:
AOC :heavy_check_mark: :x: :heavy_check_mark: :heavy_check_mark: :x:
PPOC :heavy_check_mark: :x: :heavy_check_mark: :heavy_check_mark: :x:
ACTC(3) :heavy_check_mark: :x: :heavy_check_mark: :heavy_check_mark: :x:

(1): Very unstable
(2): Needs https://openreview.net/forum?id=HyMTkQZAb implemented
(3): Incomplete implementation. β is often too high.

Sub packages

References

DQN (Deep Q Network)

DDQN (Double DQN)

Bootstrapped DQN

RPF(Randomized Prior Functions)

DDPQ(Deep Deterministic Policy Gradient)

TD3(Twin Delayed Deep Deterministic Policy Gradient)

SAC(Soft Actor Critic)

A2C (Advantage Actor Critic)

ACKTR (Actor Critic using Kronecker-Factored Trust Region)

PPO (Proximal Policy Optimization)

AOC (Advantage Option Critic)

PPOC (Proximal Option Critic)

ACTC (Actor Critic Termination Critic)

Implementaions I referenced

Thank you!

https://github.com/openai/baselines

https://github.com/ikostrikov/pytorch-a2c-ppo-acktr

https://github.com/ShangtongZhang/DeepRL

https://github.com/chainer/chainerrl

https://github.com/Thrandis/EKFAC-pytorch (for ACKTR)

https://github.com/jeanharb/a2oc_delib (for AOC)

https://github.com/mklissa/PPOC (for PPOC)

https://github.com/sfujim/TD3 (for DDPG and TD3)

https://github.com/vitchyr/rlkit (for SAC)

License

This project is licensed under Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0).

Project details


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