Problem
Research questions and friction points this paper is trying to address.
intensional functions
answer set programming
satisfiability modulo theories
functional stable model semantics
ASPMT
Functional Stable Model Semantics and Answer Set Programming Modulo Theories
🤖 AI Summary
This work addresses the limited support for intensional functions in Answer Set Programming (ASP) by proposing functional stable model semantics as a new foundation for ASP modulo theories (ASPMT). It systematically introduces intensional functions into ASPMT for the first time, enabling a deep integration of ASP with Satisfiability Modulo Theories (SMT) and establishing a formal correspondence between the two frameworks. By efficiently translating bounded ASPMT programs into SMT instances, the approach not only subsumes existing ASP–SMT integration methods as special cases but also substantially enhances ASP’s capability to model complex functional expressions.
📝 Abstract
Recently there has been an increasing interest in incorporating ``intensional'' functions in answer set programming. Intensional functions are those whose values can be described by other functions and predicates, rather than being pre-defined as in the standard answer set programming. We demonstrate that the functional stable model semantics plays an important role in the framework of ``Answer Set Programming Modulo Theories (ASPMT)'' -- a tight integration of answer set programming and satisfiability modulo theories, under which existing integration approaches can be viewed as special cases where the role of functions is limited. We show that ``tight'' ASPMT programs can be translated into SMT instances, which is similar to the known relationship between ASP and SAT.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Answer Set Programming Modulo Theories
functional stable model semantics
intensional functions
SMT
tight translation
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