A scalable weighted max-SAT implementation of propositional Etcetera Abduction

Naoya Inoue, Andrew S. Gordon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recent advances in technology for abductive reasoning, or inference to the best explanation, encourage the application of abduction to real-life commonsense reasoning problems. This paper describes Etcetera Abduction, a new implementation of logical abduction that is both grounded in probability theory and optimized using contemporary linear programming solvers. We present a Weighted Max-SAT formulation of Etcetera Abduction, which allows us to exploit highly advanced technologies developed in the field of SAT and Operations Research. Our experiments demonstrate the scalability of our proposal on a large-scale synthetic benchmark that contains up to ten thousand axioms, using one of the stateof-the-art mathematical optimizers developed in these fields. This is the first work to evaluate a SAT-based approach to abductive reasoning at this scale. The inference engine we developed has been made publicly available.

Original languageEnglish
Title of host publicationFLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference
EditorsVasile Rus, Zdravko Markov
PublisherAAAI Press
Pages62-67
Number of pages6
ISBN (Electronic)9781577357872
Publication statusPublished - 2017 Jan 1
Event30th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017 - Marco Island, United States
Duration: 2017 May 222017 May 24

Publication series

NameFLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference

Other

Other30th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2017
CountryUnited States
CityMarco Island
Period17/5/2217/5/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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