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# Fancy Gym
`fancy_gym` offers a large variety of reinforcement learning environments under the unifying interface
of [OpenAI gym](https://gym.openai.com/). We provide support (under the OpenAI gym interface) for the benchmark suites
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.ml/content/environment_creation/). We highly appreciate it, if
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).