Metadata-Version: 2.1
Name: ivy-gym
Version: 1.1.6
Summary: Fully differentiable reinforcement learning environments, written in Ivy.
Home-page: https://ivy-dl.org/gym
Author: Ivy Team
Author-email: ivydl.team@gmail.com
License: Apache 2.0
Project-URL: Docs, https://ivy-dl.org/gym/
Project-URL: Source, https://github.com/ivy-dl/gym
Description: # What is Ivy Gym?
        
        Ivy Gym opens the door for intersectional research between supervised
            learning (SL), reinforcement learning (RL), and trajectory optimization (TO), by implementing RL environments in a
            fully differentiable manner.
        
        
            Specifically, Ivy gym provides differentiable implementations of the classic control tasks from OpenAI Gym, as well
            as a new Swimmer task, which illustrates the simplicity of creating new tasks using Ivy. The differentiable nature
            of the environments means that the cumulative reward can be directly optimized for in a supervised manner, without
            need for reinforcement learning, which is the de facto approach for optimizing cumulative rewards. Ivy currently
            supports Jax, TensorFlow, PyTorch, MXNet and Numpy. Check out the [docs](https://ivy-dl.org/gym) for more info!
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Description-Content-Type: text/markdown
