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Potential Heuristics: Weakening Consistency Constraints

Title: Potential Heuristics: Weakening Consistency Constraints
Authors: Lauer, Pascal; Fišer, Daniel
Source: Proceedings of the International Conference on Automated Planning and Scheduling; Vol. 35 (2025): Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling; 218-222 ; 2334-0843 ; 2334-0835
Publisher Information: Association for the Advancement of Artificial Intelligence
Publication Year: 2025
Collection: Association for the Advancement of Artificial Intelligence: AAAI Publications
Description: In classical planning, admissible potential heuristics are computed by solving linear programs (LPs) with constraints expressing consistency and goal-awareness of the heuristic. Potential heuristics can return negative estimates. So, given a potential heuristic h^P, the actual heuristic used in search is another heuristic defined as h^P_0+(s) = max(h^P(s),0) for every reachable state s. In this paper, we reformulate the LP constraints for consistency of h^P so that they ensure consistency of h^P_0+ instead. This leads to more informative heuristics with positive impact on the overall performance in exchange for a more time and memory demanding computation using mixed integer linear programs instead of LPs.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://ojs.aaai.org/index.php/ICAPS/article/view/36121/38275; https://ojs.aaai.org/index.php/ICAPS/article/view/36121
DOI: 10.1609/icaps.v35i1.36121
Availability: https://ojs.aaai.org/index.php/ICAPS/article/view/36121; https://doi.org/10.1609/icaps.v35i1.36121
Rights: Copyright (c) 2024 Association for the Advancement of Artificial Intelligence
Accession Number: edsbas.18C142EA
Database: BASE