Possibilistic Answer Set Programming Revisited

by   Kim Bauters, et al.

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.




Characterizing and Extending Answer Set Semantics using Possibility Theory

Answer Set Programming (ASP) is a popular framework for modeling combina...

Splitting a Hybrid ASP Program

Hybrid Answer Set Programming (Hybrid ASP) is an extension of Answer Set...

Answer Set Programming Made Easy

We take up an idea from the folklore of Answer Set Programming, namely t...

Inconsistency Proofs for ASP: The ASP-DRUPE Format

Answer Set Programming (ASP) solvers are highly-tuned and complex proced...

Translating LPOD and CR-Prolog2 into Standard Answer Set Programs

Logic Programs with Ordered Disjunction (LPOD) is an extension of standa...

A Paraconsistent ASP-like Language with Tractable Model Generation

Answer Set Programming (ASP) is nowadays a dominant rule-based knowledge...

ASP(AC): Answer Set Programming with Algebraic Constraints

Weighted Logic is a powerful tool for the specification of calculations ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.