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Add gym-cellular-automata to third-party envs, reorder by stars (#412)

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2023-03-29 10:00:02 -04:00
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@@ -66,12 +66,12 @@ Highly scalable and customizable Safe Reinforcement Learning library.
Supported fork of [gym-retro](https://openai.com/research/gym-retro): turn classic video games into Gymnasium environments.
### [flappy-bird-gymnasium: A Flappy Bird environment for Gymnasium](https://github.com/markub3327/flappy-bird-gymnasium)
### [gym-cellular-automata: Cellular Automata environments](https://github.com/elbecerrasoto/gym-cellular-automata)
[![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.27.1-blue)]()
[![GitHub stars](https://img.shields.io/github/stars/markub3327/flappy-bird-gymnasium)]()
[![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.28.1-blue)]()
[![GitHub stars](https://img.shields.io/github/stars/elbecerrasoto/gym-cellular-automata)]()
A simple environment for single-agent reinforcement learning algorithms on a clone of [Flappy Bird](https://en.wikipedia.org/wiki/Flappy_Bird), the hugely popular arcade-style mobile game. Both state and pixel observation environments are available.
Environments where the agent interacts with _Cellular Automata_ by changing its cell states.
### [gym-saturation: Environments used to prove theorems](https://github.com/inpefess/gym-saturation)
@@ -87,6 +87,13 @@ An environment for guiding automated theorem provers based on saturation algorit
An environment to easily implement discrete MDPs as gym environments. Turn a set of matrices (`P_0(s)`, `P(s'| s, a)` and `R(s', s, a)`) into a gym environment that represents the discrete MDP ruled by these dynamics.
### [flappy-bird-gymnasium: A Flappy Bird environment for Gymnasium](https://github.com/markub3327/flappy-bird-gymnasium)
[![Gymnasium version dependency](https://img.shields.io/badge/Gymnasium-v0.27.1-blue)]()
[![GitHub stars](https://img.shields.io/github/stars/markub3327/flappy-bird-gymnasium)]()
A simple environment for single-agent reinforcement learning algorithms on a clone of [Flappy Bird](https://en.wikipedia.org/wiki/Flappy_Bird), the hugely popular arcade-style mobile game. Both state and pixel observation environments are available.
## Third-Party Environments using Gym
There are a large number of third-party environments using various versions of [Gym](https://github.com/openai/gym).
@@ -185,10 +192,6 @@ Reinforcement learning environments for compiler optimization tasks, such as LLV
Configurable reinforcement learning environments for testing generalization, e.g. CartPole with variable pole lengths or Brax robots with different ground frictions.
### [gym-cellular-automata: Cellular Automata environments](https://github.com/elbecerrasoto/gym-cellular-automata)
Environments where the agent interacts with _Cellular Automata_ by changing its cell states.
### [gym-sokoban: 2D Transportation Puzzles](https://github.com/mpSchrader/gym-sokoban)
The environment consists of transportation puzzles in which the player's goal is to push all boxes to the warehouse's storage locations.