DLR-RM/stable-baselines3

[Feature Request] RAINBOW

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#622 opened on Oct 22, 2021

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 (8 comments) (2 reactions) (0 assignees)Python (6,550 stars) (1,407 forks)batch import
enhancementhelp wanted

Description

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🚀 Feature

Implement RAINBOW (DQN + all extensions: noisy-net, double dqn, dueling, c51, prioritized experience replay).

closes #487 if it is implemented.

Motivation

This would allow to have DQN with all extensions while keeping DQN code simple.

  • I have checked that there is no similar issue in the repo (required)

Contributor guide

Tech stack
pythonpytorch
Domain
machine learningai
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
5
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
reinforcement learningPyTorchstable baselines3DQN
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
15
Research direction
Review the existing DQN implementation in stable baselines3/dqn/. Examine referenced issue #487 for prior discussion. Understand each extension: noisy nets, double DQN, dueling network, C51 distributional RL, and prioritized experience replay. Plan modular integration into the DQN class. Consult the Rainbow paper for algorithmic details.