[PR #1179] [CLOSED] Add pymdptoolbox to Science. #1057

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GiteaMirror · 2025-11-06T13:08:21-06:00

GiteaMirror commented

2025-11-06 13:08:21 -06:00

📋 Pull Request Information

Original PR: https://github.com/vinta/awesome-python/pull/1179
Author: @crypto-jeronimo
Created: 10/26/2018
Status: ❌ Closed

Base: master ← Head: add-python-mdp-toolbox

📝 Commits (1)

47e2175 Add pymdptoolbox to Science.

📊 Changes

1 file changed (+1 additions, -0 deletions)

View changed files

📝 README.md (+1 -0)

📄 Description

What is this Python project?

The MDP toolbox provides classes and functions for the resolution of descrete-time Markov Decision Processes. The list of algorithms that have been implemented includes backwards induction, linear programming, policy iteration, q-learning and value iteration along with several variations.

What's the difference between this Python project and similar ones?

Eight MDP algorithms implemented.
Fast array manipulation using NumPy.
Full sparse matrix support using SciPy's sparse package.
Optional linear programming support using cvxopt.

--

Anyone who agrees with this pull request could vote for it by adding a 👍 to it, and usually, the maintainer will merge it when votes reach 20.

_{🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.}

## 📋 Pull Request Information **Original PR:** https://github.com/vinta/awesome-python/pull/1179 **Author:** [@crypto-jeronimo](https://github.com/crypto-jeronimo) **Created:** 10/26/2018 **Status:** ❌ Closed **Base:** `master` ← **Head:** `add-python-mdp-toolbox` --- ### 📝 Commits (1) - [`47e2175`](https://github.com/vinta/awesome-python/commit/47e217532c61a5f170f2b05593eac703ee6e128e) Add pymdptoolbox to Science. ### 📊 Changes **1 file changed** (+1 additions, -0 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+1 -0) </details> ### 📄 Description ## What is this Python project? The MDP toolbox provides classes and functions for the resolution of descrete-time Markov Decision Processes. The list of algorithms that have been implemented includes backwards induction, linear programming, policy iteration, q-learning and value iteration along with several variations. ## What's the difference between this Python project and similar ones? - Eight MDP algorithms implemented. - Fast array manipulation using NumPy. - Full sparse matrix support using SciPy's sparse package. - Optional linear programming support using cvxopt. -- Anyone who agrees with this pull request could vote for it by adding a :+1: to it, and usually, the maintainer will merge it when votes reach **20**. --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>

GiteaMirror added the pull-request label 2025-11-06 13:08:21 -06:00

GiteaMirror closed this issue

2025-11-06 13:08:22 -06:00

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Reference: github-starred/awesome-python#1057