Abstract
Reasoning semantically in first-order logic is notoriously a challenge. This paper surveys a selection of semantically-guided or model-based methods that aim at meeting aspects of this challenge. For first-order logic we touch upon resolution-based methods, tableaux-based methods, DPLL-inspired methods, and we give a preview of a new method called SGGS, for Semantically-Guided Goal-Sensitive reasoning. For first-order theories we highlight hierarchical and locality-based methods, concluding with the recent Model-Constructing satisfiability calculus.
Dedicated to
José Meseguer,
friend and colleague.
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Notes
- 1.
- 2.
The problem in Examples 10 and 11 appeared in the slides of a talk entitled “Arithmetic and Optimization @ MCsat” presenting joint work by Leonardo de Moura, Dejan Jovanović, and Grant Olney Passmore, and given by Leonardo de Moura at a Schloss Dagsthul Seminar on “Deduction and Arithmetic” in October 2013.
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Acknowledgments
The first author thanks David Plaisted, for starting the research on SGGS and inviting her to join in August 2008; and Leonardo de Moura, for the discussions on MCsat at Microsoft Research in Redmond in June 2013. The third author’s work was partially supported by the German Research Council (DFG) as part of the Transregional Collaborative Research Center “Automatic Verification and Analysis of Complex Systems” (SFB/TR 14 AVACS, www.avacs.org).
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Bonacina, M.P., Furbach, U., Sofronie-Stokkermans, V. (2015). On First-Order Model-Based Reasoning. In: Martí-Oliet, N., Ölveczky, P., Talcott, C. (eds) Logic, Rewriting, and Concurrency. Lecture Notes in Computer Science(), vol 9200. Springer, Cham. https://doi.org/10.1007/978-3-319-23165-5_8
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