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deepr's Introduction

DeepR

A Deep Reinforcement Learning pipeline for Rust.

Goal

NOTE: Right now this is still in it's early stages and is undergoing a lot of changes The goal of Deepr is to simplify the process of developing Deep Reinforcement Learning(DRL) models. Ideally someone without any AI experience should be able to easily create state of the art DRL models and then all they have to do is host them somewhere.

Currently this crate supports Softmax Deep Double Deterministic Policy Gradients (SD3 with pytorch.

deepr's People

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deepr's Issues

Tensorflow Support

Right now the model is generated using PyTorch. This was simply because I've used PyTorch more and wanted to get something working fast. It would be good to also offer the option to use Tensorflow.

Ideally we could have a feature flag that allows the user to choose which backend they want use.

Examples

Short Term

Implement some basic examples so people can see how to use the crate. The easiest way is probably to do some implementations for the OpenAI Gym problems.

Longer Term (but not to long)

I would also like to do a full tutorial/implementation on a real life problem that covers everything from setting up the environment -> model generation -> model deployment.

Additional Algorithms

Right now we use SD3 which is pretty state of the art in this space. Still we should implement some more options like TRPO, SAC, HER, etc.

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