Work

Potential Heuristics: Weakening Consistency Constraints

Year: 2025

Type: conference-paper

Abstract: 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.

Source: Proceedings of the International Conference on Automated Planning and Scheduling

DOI: 10.1609/icaps.v35i1.36121

Authors: Pascal Lauer, Daniel Fišer

Institutions: Australian National University, Saarland University, Aalborg University

Language: English

Topic: AI-based Problem Solving and Planning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Deutsche Forschungsgemeinschaft

Awards: G1951765764, SFB 1102: Informationsdichte und sprachliche Kodierung