JOURNAL ARTICLE

The FF Heuristic for Lifted Classical Planning

Augusto B. CorrêaFlorian PommereningMalte HelmertGuillem Francès

Year: 2022 Journal:   Proceedings of the AAAI Conference on Artificial Intelligence Vol: 36 (9)Pages: 9716-9723   Publisher: Association for the Advancement of Artificial Intelligence

Abstract

Heuristics for lifted planning are not yet as informed as the best heuristics for ground planning. Recent work introduced the idea of using Datalog programs to compute the additive heuristic over lifted tasks. Based on this work, we show how to compute the more informed FF heuristic in a lifted manner. We extend the Datalog program with executable annotations that can also be used to define other delete-relaxation heuristics. In our experiments, we show that a planner using the lifted FF implementation produces state-of-the-art results for lifted planners. It also reduces the gap to state-of-the-art ground planners in domains where grounding is feasible.

Keywords:
Heuristics Planner Heuristic Executable Computer science Datalog Relaxation (psychology) State (computer science) Mathematical optimization Theoretical computer science Algorithm Artificial intelligence Mathematics Programming language

Metrics

7
Cited By
0.82
FWCI (Field Weighted Citation Impact)
28
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

AI-based Problem Solving and Planning
Physical Sciences →  Computer Science →  Artificial Intelligence
Logic, Reasoning, and Knowledge
Physical Sciences →  Computer Science →  Artificial Intelligence
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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