A collection of useful environments for testing Reinforcement Learning algorithms. Designed (mostly) with discrete, graph-based methods in mind.
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Updated
Mar 5, 2024 - Python
A collection of useful environments for testing Reinforcement Learning algorithms. Designed (mostly) with discrete, graph-based methods in mind.
Python implementation of Hierarchies of Abstract Machines (HAMs)
OpenAI's ES used in a feudal hrl style
Pytorch implementation of Hierarchical Intentional-Unintentional Soft Actor-Critic (HIU-SAC) algorithm
Pytorch code for Hierarchical Latent Space Learning (HLSL)
Spring 2021 - CSE 574 Project
Implementation of STAR from the paper "Reconciling Spatial and Temporal Abstractions for Goal Representation" (ICLR 2024)
An interface for hierarchical environments.
A project for researching a complex and long-horizon manipulation task especially focused on hierarchically stacking blocks.
Implementation of the Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning by Tianmin Shu, Caiming Xiong, and Richard Socher
SynGameZero – Flowsheet Synthesis in a Game environment with Zero Knowledge
Video Input Generative Adversarial Imitation Learning
Modular Deep RL infrastructure in PyTorch
The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
Master thesis work: explaining deep reinforcement learning policies
Implementation of Option-Critic Algorithm - https://arxiv.org/abs/1609.05140
Python implementation of Hierarchies of Abstract Machine (HAM) as a python coroutine. (Abandoned, new repo at Juno-T/pyham)
Reinforcement learning algorithms constrained by a partial program
Feudal Reinforcement Learning with Q learning
Supplemental materials for "Playing FPS Games with Environment-Aware Hierarchical Reinforcement Learning", accepted by IJCAI'19
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