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Add DACBench third party environment (#451)

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Elliot Tower
2023-04-15 19:34:42 -04:00
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docs/environments/third_party_environments.md
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@@ -73,6 +73,13 @@ Supported fork of [gym-retro](https://openai.com/research/gym-retro): turn class
Environments where the agent interacts with _Cellular Automata_ by changing its cell states.
### [DACBench: a benchmark for Dynamic Algorithm Configuration](https://github.com/automl/DACBench)
[![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.26.3-blue)]()
[![GitHub stars](https://img.shields.io/github/stars/automl/DACBench)]()
A benchmark library for [Dynamic Algorithm Configuration](https://www.automl.org/dynamic-algorithm-configuration/). Its focus is on reproducibility and comparability of different DAC methods as well as easy analysis of the optimization process.
### [gym-saturation: Environments used to prove theorems](https://github.com/inpefess/gym-saturation)
[![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.27.1-blue)]()
@@ -127,7 +134,6 @@ A simple environment using [PyBullet](https://github.com/bulletphysics/bullet3)
Mars Explorer is a Gym compatible environment designed and developed as an initial endeavor to bridge the gap between powerful Deep Reinforcement Learning methodologies and the problem of exploration/coverage of an unknown terrain.
### [robo-gym: Real-world and simulation robotics](https://github.com/jr-robotics/robo-gym)
Robo-gym provides a collection of reinforcement learning environments involving robotic tasks applicable in both simulation and real-world robotics.