TY - GEN
T1 - Towards Search Node-Specific HTN Heuristics
AU - Yuan, Lijia
AU - Bercher, Pascal
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - Heuristics
KW - HTN planning
KW - Progression search
UR - https://www.scopus.com/pages/publications/105023819878
U2 - 10.1007/978-981-95-4972-6_34
DO - 10.1007/978-981-95-4972-6_34
M3 - Conference Paper
AN - SCOPUS:105023819878
SN - 9789819549719
T3 - Lecture Notes in Computer Science
SP - 439
EP - 452
BT - AI 2025
A2 - Liu, Miaomiao
A2 - Yu, Xin
A2 - Xu, Chang
A2 - Song, Yiliao
PB - Springer Science+Business Media B.V.
T2 - 38th Australasian Joint Conference on Artificial Intelligence, AI 2025
Y2 - 1 December 2025 through 5 December 2025
ER -