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Towards Search Node-Specific HTN Heuristics

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review

Abstract

While effective in hierarchical task network (HTN) planning, heuristic search currently relies on few pre-selected heuristics. However, during progression-based search, many search nodes exhibit specific properties, e.g., they may become totally ordered or acyclic, allowing for the application of specialized heuristics. For these search nodes, we conducted an experimental evaluation, employing reachability analysis to examine the special cases encountered during search. Measuring how often various special cases occur informs us which heuristics developed for special cases – selected on a per-search node basis – are most promising. As a side contribution, we propose a slight modification of a technical definition used to define properties of the task hierarchy.

Original languageEnglish
Title of host publicationAI 2025
Subtitle of host publicationAdvances in Artificial Intelligence - 38th Australasian Joint Conference on Artificial Intelligence, AI 2025, Proceedings
EditorsMiaomiao Liu, Xin Yu, Chang Xu, Yiliao Song
PublisherSpringer Science+Business Media B.V.
Pages439-452
Number of pages14
ISBN (Electronic)9789819549726
ISBN (Print)9789819549719
DOIs
Publication statusPublished - 2026
Event38th Australasian Joint Conference on Artificial Intelligence, AI 2025 - Canberra, Australia
Duration: 1 Dec 2025 → 5 Dec 2025

Publication series

NameLecture Notes in Computer Science
Volume16371 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference38th Australasian Joint Conference on Artificial Intelligence, AI 2025
Country/TerritoryAustralia
CityCanberra
Period1/12/25 → 5/12/25

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