Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.
-
Updated
Sep 9, 2021 - Python
Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.
Official implementation of Zero-Hero paper
A Python package that provides a simple framework for working with Options in Reinforcement Learning.
[IJCAI 2024] Constrained Intrinsic Motivation for Reinforcement Learning
Adaptation of original "Contrastive Intrinsic Control for Unsupervised Skill Discovery" implementation to OpenAI Gym
"Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills" (ICML 2020)
This repository contains an updated implementation of the DIAYN algorithm compatible with newer versions of MuJoCo and OpenAI Gym
Pytorch code for Hierarchical Latent Space Learning (HLSL)
Add a description, image, and links to the skill-discovery topic page so that developers can more easily learn about it.
To associate your repository with the skill-discovery topic, visit your repo's landing page and select "manage topics."