HierarchyCraft: A Benchmark Builder for Hierarchical Reasoning

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Authors: Mathis Federico, Shang Wang, Yuxuan Li, Matthew Taylor
Cited by: 0

Abstract

HierarchyCraft (hcraft for short) is a Python library designed to create arbitrary hierarchical environments that are compatible with both the OpenAI Gym Reinforcement Learning Framework and AIPlan4EU Unified Planning Framework. This library enables users to easily create complex hierarchical structures that can be used to test and develop various reinforcement learning or planning algorithms. In environments built with HierarchyCraft the agent (player) has an inventory and can navigate into abstract zones that themselves have inventories. The action space of HierarchyCraft environments consists of sub-tasks, referred to as Transformations, as opposed to detailed movements and controls. But each Transformations has specific requirements to be valid (eg. have enought of an item, be in the right place), and these requirements may necessitate the execution of other Transformations first, inherently creating a hierarchical structure in HierarchyCraft environments. This concept is visually represented by the Requirements graph depicting the hierarchical relationships within each HierarchyCraft environment. The Requirements graph is directly constructed from the list of Transformations composing the environement. More details about requirements graph can be found in the documentation at hcraft.requirements and example of requirements graph for some HierarchyCraft environements can be found in hcraft.examples.

Fields of Study & Subjects

Reinforcement Learning in Robotics AI-based Problem Solving and Planning Artificial Intelligence in Games

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
9 March 2026
Language
EN