Open AccessProceedings Article
Extending answer set programming using generalized possibilistic logic
Didier Dubois,Henri Prade,Steven Schockaert +2 more
- 25 Jul 2015
- pp 8-12
TL;DR: How a recent generalization of possibilistic logic (GPL) can be used to characterize the semantics of answer set programming and offers a natural way of dealing with uncertainty in answer set programs is explained.
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Abstract: Answer set programming (ASP) is a form of logic programming in which negation-as-failure is defined in a purely declarative way, based on the notion of a stable model. This short paper briefly explains how a recent generalization of possibilistic logic (GPL) can be used to characterize the semantics of answer set programming. This characterization has several advantages over existing characterizations of the stable model semantics. First, unlike reduct-based approaches, it does not rely on a syntactic procedure: we can directly characterize answer sets based on the minimally specific models of a GPL theory. Second, GPL enables us to study extensions of ASP in an intuitive way: unlike in existing generalizations of ASP such as equilibrium logic and autoepistemic logic, all formulas in GPL have a meaning which is intuitively clear. Finally, being based on possibilistic logic, GPL offers a natural way of dealing with uncertainty in answer set programs.
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Citations
L’IA symbolique et le dépassement de la logique classique
Henri Prade
TL;DR: This paper explores the intersection of symbolic AI and classical logic, examining how symbolic representations can transcend traditional logical frameworks, enabling more expressive and flexible reasoning mechanisms in artificial intelligence systems.
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TL;DR: In this paper, the authors give a reconstruction of non-monotonic logic as a model of an Ideally rational agent's reasoning about his own beliefs, and define an Intuitively based semantics for which they can show autoeplstemlc logic to be both sound and complete.
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Joseph Y. Halpern
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TL;DR: This work provides axiom systems that are sound and complete in cases where a complete axiomatization is possible, and shows that they do allow us to capture a great deal of interesting reasoning about probability.
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TL;DR: A simplified version of that propositional nonmonotonic logic is described, it is shown how quantifiers can be included in it, and its relation to circumscription and default logic, to logic programming, and to the theory of epistemic queries developed by Hector Levesque and Ray Reiter is studied.
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