Possibilistic Answer Set Programming Revisited


Autoria(s): Bauters, Kim; Schockaert, Steven; Cock, Martine De; Vermeir, Dirk
Contribuinte(s)

Grünwald, Peter

Spirtes, Peter

Data(s)

2010

Resumo

Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an application point of view, existing semantics are not well-motivated, and do not always yield intuitive results. To develop a more suitable semantics, we first introduce a characterization of answer sets of classical ASP programs in terms of possibilistic logic where an ASP program specifies a set of constraints on possibility distributions. This characterization is then naturally generalized to define answer sets of PASP programs. We furthermore provide a syntactic counterpart, leading to a possibilistic generalization of the well-known Gelfond-Lifschitz reduct, and we show how our framework can readily be implemented using standard ASP solvers.

Identificador

http://pure.qub.ac.uk/portal/en/publications/possibilistic-answer-set-programming-revisited(19508aac-9a2a-4f27-a707-9ae2bc306485).html

Idioma(s)

eng

Publicador

AUAI Press

Direitos

info:eu-repo/semantics/closedAccess

Fonte

Bauters , K , Schockaert , S , Cock , M D & Vermeir , D 2010 , Possibilistic Answer Set Programming Revisited . in P Grünwald & P Spirtes (eds) , Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) . AUAI Press , The 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010) , California , United States , 8-11 July .

Tipo

contributionToPeriodical