An Answer Set Solver for non-Herbrand Programs: Progress Report

In this paper we propose an extension of Answer Set Programming (ASP) by non-Herbrand functions, i.e. functions over non-Herbrand domains, and describe a solver for the new language. Our approach stems for our interest in practical applications, and from the corresponding need to compute the answer sets of programs with non-Herbrand functions efficiently. Our extension of ASP is such that the semantics of the new language is obtained by a comparatively small change to the ASP semantics from [8]. This makes it possible to modify a state-of-the-art ASP solver in an incremental fashion, and use it for the computation of the answer sets of (a large class of) programs of the new language. The computation is rather efficient, as demonstrated by our experimental evaluation

Integration Schemas for Constraint Answer Set Programming: a Case Study

Recently, researchers in answer set programming and constraint programming spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts resulted in a new research area: constraint answer set programming (CASP). CASP languages and systems proved to be largely successful at providing efficient solutions to problems involving hybrid reasoning tasks, such as scheduling problems with elements of planning. Yet, the development of CASP systems is difficult, requiring non-trivial expertise in multiple areas. This suggests a need for a study identifying general development principles of hybrid systems. Once these principles and their implications are well understood, the development of hybrid languages and systems may become a wellestablished and well-understood routine process. As a step in this direction, in this paper we conduct a case study aimed at evaluating various integration schemas of CASP methods

CASP Solutions for Planning in Hybrid Domains

CASP is an extension of ASP that allows for numerical constraints to be added in the rules. PDDL+ is an extension of the PDDL standard language of automated planning for modeling mixed discrete-continuous dynamics. In this paper, we present CASP solutions for dealing with PDDL+ problems, i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP CASP solver in order to solve CASP programs arising from PDDL+ domains. An experimental analysis, performed on well-known linear and non-linear variants of PDDL+ domains, involving various configurations of the EZCSP solver, other CASP solvers, and PDDL+ planners, shows the viability of our solution.Comment: Under consideration in Theory and Practice of Logic Programming (TPLP