Python implementation of Hierarchies of Abstract Machines (HAMs)
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Updated
Sep 18, 2022 - Python
Python implementation of Hierarchies of Abstract Machines (HAMs)
A collection of useful environments for testing Reinforcement Learning algorithms. Designed (mostly) with discrete, graph-based methods in mind.
Pytorch implementation of Hierarchical Intentional-Unintentional Soft Actor-Critic (HIU-SAC) algorithm
Pytorch code for Hierarchical Latent Space Learning (HLSL)
An interface for hierarchical environments.
A project for researching a complex and long-horizon manipulation task especially focused on hierarchically stacking blocks.
Spring 2021 - CSE 574 Project
Implementation of the Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning by Tianmin Shu, Caiming Xiong, and Richard Socher
Video Input Generative Adversarial Imitation Learning
This repository is the official implementation of "Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks."(NeurIPS 2020)
Posterior Goal Sampling for Hierarchical Reinforcement Learning
Modular Deep RL infrastructure in PyTorch
Python implementation of Hierarchies of Abstract Machine (HAM) as a python coroutine. (Abandoned, new repo at Juno-T/pyham)
An end-to-end differentiable hierarchical reinforcement learning agent based on continuous sub-policy attention.
hdrqn
Framework for developing Actor-Critic deep RL algorithms (A3C, A2C, PPO, GAE, etc..) in different environments (OpenAI's Gym, Rogue, Sentiment Analysis, Car Controller, etc..) with continuous and discrete action spaces.
Anchor: The achieved goal to replace the subgoal for hierarchical reinforcement learning
This repo implements the HIRO algorithm for Hierarchical Reinforcement Learning in the original environment using Tensorflow 2.
A public release of my RL research.
Tasks with combinatorial structure embedded in MuJoCo robotics environments.
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