rl-worlds


Namerl-worlds JSON
Version 0.0.1 PyPI version JSON
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home_pageNone
SummaryNone
upload_time2024-12-12 13:47:02
maintainerNone
docs_urlNone
authorFalguni Das Shuvo
requires_python>=3.8
licenseMIT License Copyright (c) 2024 Falguni Das Shuvo Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
keywords reinforcement learning rl environment grid world windy grid world random walk
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # RL-Worlds    [![Upload Python Package](https://github.com/shuvoxcd01/RL-Worlds/actions/workflows/python-publish.yml/badge.svg)](https://github.com/shuvoxcd01/RL-Worlds/actions/workflows/python-publish.yml)

**RL-Worlds** is a collection of reinforcement learning (RL) environments designed to help researchers, students, and enthusiasts study and implement RL algorithms. All environments in this repository are built to adhere to the [Gymnasium](https://gymnasium.farama.org/) environment format, making them compatible with a wide range of RL libraries and tools.

---

## Available Environments

1. 🐾 Random Walk

2. 🌟 Thousand States Random Walk

3. 🌍 Grid World

4. 🌬️ Windy Grid World

            

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