Pseudo-Boolean Proof Logging for Optimal Classical Planning
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866909599461801984 |
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| author | Dold, Simon Helmert, Malte Nordström, Jakob Röger, Gabriele Schindler, Tanja |
| author_facet | Dold, Simon Helmert, Malte Nordström, Jakob Röger, Gabriele Schindler, Tanja |
| contents | We introduce lower-bound certificates for classical planning tasks, which can be used to prove the unsolvability of a task or the optimality of a plan in a way that can be verified by an independent third party. We describe a general framework for generating lower-bound certificates based on pseudo-Boolean constraints, which is agnostic to the planning algorithm used.
As a case study, we show how to modify the $A^{*}$ algorithm to produce proofs of optimality with modest overhead, using pattern database heuristics and $h^\textit{max}$ as concrete examples. The same proof logging approach works for any heuristic whose inferences can be efficiently expressed as reasoning over pseudo-Boolean constraints. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_18443 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Pseudo-Boolean Proof Logging for Optimal Classical Planning Dold, Simon Helmert, Malte Nordström, Jakob Röger, Gabriele Schindler, Tanja Artificial Intelligence We introduce lower-bound certificates for classical planning tasks, which can be used to prove the unsolvability of a task or the optimality of a plan in a way that can be verified by an independent third party. We describe a general framework for generating lower-bound certificates based on pseudo-Boolean constraints, which is agnostic to the planning algorithm used. As a case study, we show how to modify the $A^{*}$ algorithm to produce proofs of optimality with modest overhead, using pattern database heuristics and $h^\textit{max}$ as concrete examples. The same proof logging approach works for any heuristic whose inferences can be efficiently expressed as reasoning over pseudo-Boolean constraints. |
| title | Pseudo-Boolean Proof Logging for Optimal Classical Planning |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2504.18443 |