From 55f84da5e1c6289e5b03611634b6c8a2bbbf631d Mon Sep 17 00:00:00 2001 From: Dominik Roth Date: Tue, 27 Jun 2023 21:39:03 +0200 Subject: [PATCH] A fancy icon for fancy gym --- README.md | 24 +++++++------ icon.svg | 101 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 115 insertions(+), 10 deletions(-) create mode 100644 icon.svg diff --git a/README.md b/README.md index 4db4f69..6988f38 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,17 @@ -# Fancy Gym +

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+ Fancy Gym +
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-`fancy_gym` offers a large variety of reinforcement learning environments under the unifying interface -of [OpenAI gym](https://gymlibrary.dev/). We provide support (under the OpenAI gym interface) for the benchmark suites -[DeepMind Control](https://deepmind.com/research/publications/2020/dm-control-Software-and-Tasks-for-Continuous-Control) -(DMC) and [Metaworld](https://meta-world.github.io/). If those are not sufficient and you want to create your own custom -gym environments, use [this guide](https://www.gymlibrary.dev/content/environment_creation/). We highly appreciate it, if -you would then submit a PR for this environment to become part of `fancy_gym`. -In comparison to existing libraries, we additionally support to control agents with movement primitives, such as Dynamic -Movement Primitives (DMPs) and Probabilistic Movement Primitives (ProMP). +`fancy_gym` offers a large variety of reinforcement learning environments under the unifying interface of [Gymnasium](https://gymnasium.farama.org/). + +We provide support (under the Gymnasium interface) for the benchmark suites [DeepMind Control](https://deepmind.com/research/publications/2020/dm-control-Software-and-Tasks-for-Continuous-Control) (DMC) and [Metaworld](https://meta-world.github.io/). If those are not sufficient and you want to create your own custom gym environments, use [this guide] https://www.gymlibrary.dev/content/environment_creation/). We highly appreciate it, if you would then submit a PR for this environment to become part of `fancy_gym`. + +In comparison to existing libraries, we additionally support to control agents with movement primitives, such as Dynamic Movement Primitives (DMPs) and Probabilistic Movement Primitives (ProMP). ## Movement Primitive Environments (Episode-Based/Black-Box Environments) @@ -73,7 +77,7 @@ for i in range(1000): if done: obs = env.reset() -``` +``` When using `dm_control` tasks we expect the `env_id` to be specified as `dmc:domain_name-task_name` or for manipulation tasks as `dmc:manipulation-environment_name`. For `metaworld` tasks, we require the structure `metaworld:env_id-v2`, our diff --git a/icon.svg b/icon.svg new file mode 100644 index 0000000..64ec435 --- /dev/null +++ b/icon.svg @@ -0,0 +1,101 @@ + + + +