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A Python package that provides a simple framework for working with Options in Reinforcement Learning.

Automated mathematical theorem formulation deduced from a provided set of axioms. Builds upon the HRL theorem generator.

Locomotion HRL envs in pybullet

Python implementation of Hierarchies of Abstract Machines (HAMs)

Feudal Reinforcement Learning with Q learning

Package implementing recursive pseudo-dimensional reductions of RL state spaces for the synthetic creation of hierarchical reinforcement learning (HRL) training curricula.

Anchor: The achieved goal to replace the subgoal for hierarchical reinforcement learning

Implementation of Option-Critic Algorithm - https://arxiv.org/abs/1609.05140

Code of Paper: ToSCA: Leveraging Hierarchical Reinforcement Learning on Temporal and Strategic Abstractions of Conversational Agents (under review)