Curt-Park/rainbow-is-all-you-need
A step-by-step tutorial implementing DQN, Double DQN, PER, Dueling Net, NoisyNet, Categorical DQN, N-step Learning, and Rainbow in PyTorch.
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This is a hands-on educational repository that walks through the evolution of Deep Q-Network algorithms from basic DQN to the full Rainbow algorithm. Each chapter covers theoretical backgrounds followed by object-oriented implementations using PyTorch. The tutorial covers key RL innovations including prioritized experience replay, dueling networks, noisy networks, categorical DQN, and n-step learning. It runs interactively via marimo notebooks in the cloud.
Frequently asked
- What is Curt-Park/rainbow-is-all-you-need?
- A step-by-step tutorial implementing DQN, Double DQN, PER, Dueling Net, NoisyNet, Categorical DQN, N-step Learning, and Rainbow in PyTorch.
- Is rainbow-is-all-you-need open source?
- Yes — Curt-Park/rainbow-is-all-you-need is open source, released under the MIT license.
- What language is rainbow-is-all-you-need written in?
- Curt-Park/rainbow-is-all-you-need is primarily written in Python.
- How popular is rainbow-is-all-you-need?
- Curt-Park/rainbow-is-all-you-need has 2k stars on GitHub.
- Where can I find rainbow-is-all-you-need?
- Curt-Park/rainbow-is-all-you-need is on GitHub at https://github.com/Curt-Park/rainbow-is-all-you-need.