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Full-Text Articles in Physical Sciences and Mathematics
Constraint Answer Set Programming, Yuliya Lierler
Constraint Answer Set Programming, Yuliya Lierler
Computer Science Faculty Publications
Constraint answer set programming (CASP) is a novel, promising direction of research whose roots go back to propositional satisfiability (SAT). SAT solvers are efficient tools for solving boolean constraint satisfaction problems that arise in different areas of computer science, including software and hardware verification. Some constraints are more naturally expressed by non-boolean constructs. Satisfiability modulo theories (SMT) extends boolean satisfiability by the integration of non-boolean symbols defined by a background theory in another formalism, such as a constraint processing language. Answer set programming (ASP) extends computational methods of SAT in yet another way, inspired by ideas from knowledge representation, logic …
Representing First-Order Causal Theories By Logic Programs, Paolo Ferrarris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz, Fangkai Yang
Representing First-Order Causal Theories By Logic Programs, Paolo Ferrarris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz, Fangkai Yang
Computer Science Faculty Publications
Nonmonotonic causal logic, introduced by McCain and Turner (McCain, N. and Turner, H. 1997. Causal theories of action and change. In Proceedings of National Conference on Artificial Intelligence (AAAI), Stanford, CA, 460–465) became the basis for the semantics of several expressive action languages. McCain's embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries about actions described in such languages. In this paper we extend this embedding to nondefinite theories and to the first-order causal logic.
A Tarskian Informal Semantics For Answer Set Programming, Marc Denecker, Yuliya Lierler, Miroslaw Truszczyński, Joost Vennekens
A Tarskian Informal Semantics For Answer Set Programming, Marc Denecker, Yuliya Lierler, Miroslaw Truszczyński, Joost Vennekens
Computer Science Faculty Proceedings & Presentations
In their seminal papers on stable model semantics, Gelfond and Lifschitz introduced ASP by casting programs as epistemic theories, in which rules represent statements about the knowledge of a rational agent. To the best of our knowledge, theirs is still the only published systematic account of the intuitive meaning of rules and programs under the stable semantics. In current ASP practice, however, we find numerous applications in which rational agents no longer seem to play any role. Therefore, we propose here an alternative explanation of the intuitive meaning of ASP programs, in which they are not viewed as statements about …
Weighted-Sequence Problem: Asp Vs Casp And Declarative Vs Problem-Oriented Solving, Yuliya Lierler, Shaden Smith
Weighted-Sequence Problem: Asp Vs Casp And Declarative Vs Problem-Oriented Solving, Yuliya Lierler, Shaden Smith
Computer Science Faculty Proceedings & Presentations
Search problems with large variable domains pose a challenge to current answer-set programming (ASP) systems as large variable domains make grounding take a long time, and lead to large ground theories that may make solving infeasible. To circumvent the “grounding bottleneck” researchers proposed to integrate constraint solving techniques with ASP in an approach called constraint ASP (CASP). In the paper, we evaluate an ASP system clingo and a CASP system clingcon on a handcrafted problem involving large integer domains that is patterned after the database task of determining the optimal join order. We find that search methods used by clingo …
On The Relation Of Constraint Answer Set Programming Languages And Algorithms, Yuliya Lierler
On The Relation Of Constraint Answer Set Programming Languages And Algorithms, Yuliya Lierler
Computer Science Faculty Proceedings & Presentations
Recently a logic programming language AC was proposed by Mellarkod et al. (2008) to integrate answer set programming (ASP) and constraint logic programming. Similarly, Gebser et al. (2009) proposed a CLINGCON language integrating ASP and finite domain constraints. These languages allow new efficient inference algorithms that combine traditional ASP procedures and other methods in constraint programming. In this paper we show that a transition system introduced by Nieuwenhuis et al. (2006) to model SAT solvers can be extended to model the “hybrid” ACSOLVER algorithm by Mellarkod et al. developed for simple AC programs and the CLINGCON algorithm by Gebser et …
Practical And Methodological Aspects Of The Use Of Cutting-Edge Asp Tools, Marcello Balduccini, Yuliya Lierler
Practical And Methodological Aspects Of The Use Of Cutting-Edge Asp Tools, Marcello Balduccini, Yuliya Lierler
Computer Science Faculty Proceedings & Presentations
In the development of practical applications of answer set programming (ASP), encodings that use well-established solvers such as CLASP and DLV are sometimes affected by scalability issues. In those situations, one can resort to more sophisticated ASP tools exploiting, for instance, incremental and constraint ASP. However, today there is no specific methodology for the selection or use of such tools. In this paper we describe how we used such cutting-edge ASP tools on challenging problems from the Third Answer Set Programming Competition. We view this paper as a first step in the development of a general methodology for the use …
Surviving Solver Sensitivity: An Asp Practitioner’S Guide, Bryan Silverthorn, Yuliya Lierler, Marius Schneider
Surviving Solver Sensitivity: An Asp Practitioner’S Guide, Bryan Silverthorn, Yuliya Lierler, Marius Schneider
Computer Science Faculty Proceedings & Presentations
Answer set programming (ASP) is a declarative programming formalism that allows a practitioner to specify a problem without describing an algorithm for solving it. In ASP, the tools for processing problem specifications are called answer set solvers. Because specified problems are often NP complete, these systems often require significant computational effort to succeed. Furthermore, they offer different heuristics, expose numerous parameters, and their running time is sensitive to the configuration used. Portfolio solvers and automatic algorithm configuration systems are recent attempts to automate the problem of manual parameter tuning, and to mitigate the burden of identifying the right solver configuration. …