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Algorithm and utilities for deep reinforcement learning

Project description


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Reinforcement learning utilities and algrithm implementations using PyTorch.

API documentation


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 implemented
(3): Incomplete implementation. β is often too high.

Sub packages


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! (for ACKTR) (for AOC) (for PPOC) (for DDPG and TD3) (for SAC)


This project is licensed under Apache License, Version 2.0 (LICENSE-APACHE or

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