BLAST: Bit-Blasting Numbers for Classical Planning (Extended Abstract)

It is well known that numeric planning can be made decidable if the domain of all numeric state variables is finite. This bounded formulation can be polynomially compiled into classical planning with Boolean conditions and conditional effects preserving the plan size exactly. However, it remains unclear whether this compilation has any practical utility. To explore this aspect, this work revisits the theoretical compilation framework from a practical perspective, focusing on the fragment of simple numeric planning. Specifically, we introduce three different compilations. The first, called one-hot, aims to systematise the current practice among planning practitioners of modelling numeric planning through classical planning. The other two, termed binary compilations, extend and specialise the logarithmic encoding introduced in previous literature. Our experimental analysis reveals that the overly complex logarithmic encoding can, surprisingly, be made practical with some representational expedients. Among these, the use of axioms is particularly crucial. Furthermore, we identify a class of mildly numeric planning problems where a classical planner, i.e., LAMA, when run on the compiled problem, is highly competitive with state-of-the-art numeric planners.

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Publication Details

Journal
Proceedings of the International Symposium on Combinatorial Search
Published
2025-07-19
DOI
https://doi.org/10.1609/socs.v18i1.36002
Primary Topic
AI-based Problem Solving and Planning
Type
article
Field-Weighted Citation Impact
0.00

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article

BLAST: Bit-Blasting Numbers for Classical Planning (Extended Abstract)

Francesco Percassi, Luigi Bonassi, Enrico Scala
Proceedings of the International Symposium on Combinatorial Search
AI-based Problem Solving and Planning
article

BLAST: Bit-Blasting Numbers for Classical Planning (Extended Abstract)

Francesco Percassi, Luigi Bonassi, Enrico Scala
article en

Abstract

It is well known that numeric planning can be made decidable if the domain of all numeric state variables is finite. This bounded formulation can be polynomially compiled into classical planning with Boolean conditions and conditional effects preserving the plan size exactly. However, it remains unclear whether this compilation has any practical utility. To explore this aspect, this work revisits the theoretical compilation framework from a practical perspective, focusing on the fragment of simple numeric planning. Specifically, we introduce three different compilations. The first, called one-hot, aims to systematise the current practice among planning practitioners of modelling numeric planning through classical planning. The other two, termed binary compilations, extend and specialise the logarithmic encoding introduced in previous literature. Our experimental analysis reveals that the overly complex logarithmic encoding can, surprisingly, be made practical with some representational expedients. Among these, the use of axioms is particularly crucial. Furthermore, we identify a class of mildly numeric planning problems where a classical planner, i.e., LAMA, when run on the compiled problem, is highly competitive with state-of-the-art numeric planners.

Proceedings of the International Symposium on Combinatorial SearchVol. 18
University of Huddersfield (GB), University of Oxford (GB), University of Brescia (IT)
UK Research and Innovation
Openalex Percentile: Top 91%
AI-based Problem Solving and Planning
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BLAST: Bit-Blasting Numbers for Classical Planning (Extended Abstract) — Francesco Percassi, Luigi Bonassi, et al. · Proceedings of the International Symposium on Combinatorial Search (2025) | TGRS Research Map | TGRS