Combining Answer Set Programming and domain heuristics for solving hard industrial problems (Application Paper)

Dodaro, Carmine; Gasteiger, Philip; Leone, Nicola; Musitsch, Benjamin; Ricca, Francesco; Shchekotykhin, Kostyantyn

doi:10.1017/s1471068416000284

Cited by 39 publications

(37 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Answer set programming (ASP ;Niemelä 1999;Marek and Truszczyński 1999;Baral 2010;Brewka et al 2011;Janhunen and Niemelä 2016;Lifschitz 2016) is today a popular logic-based knowledge representation and constraint programming framework with constructs specifically designed for industrial applications (Gebser et al 2013;Dodaro et al 2016). In ASP, knowledge is expressed via logic programs, also referred to as ASP programs, or simply programs.…”

Section: Introductionmentioning

confidence: 99%

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

Self Cite

View full text Add to dashboard Cite

Answer Set Programming (ASP) is a logic-based knowledge representation framework, supporting-among other reasoning modes-the central task of query answering. In the propositional case, query answering amounts to computing cautious consequences of the input program among the atoms in a given set of candidates, where a cautious consequence is an atom belonging to all stable models. Currently, the most efficient algorithms either iteratively verify the existence of a stable model of the input program extended with the complement of one candidate, where the candidate is heuristically selected, or introduce a clause enforcing the falsity of at least one candidate, so that the solver is free to choose which candidate to falsify at any time during the computation of a stable model. This paper introduces new algorithms for the computation of cautious consequences, with the aim of driving the solver to search for stable models discarding more candidates. Specifically, one of such algorithms enforces minimality on the set of true candidates, where different notions of minimality can be used, and another takes advantage of unsatisfiable cores computation. The algorithms are implemented in WASP, and experiments on benchmarks from the latest ASP competitions show that the new algorithms perform better than the state of the art. (Under consideration for acceptance in TPLP).

show abstract

Section: Introductionmentioning

confidence: 99%

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

Self Cite

View full text Add to dashboard Cite

show abstract

“…There is a number of approaches to embed heuristic knowledge into the ASP solving process. HWASP [10] extends the WASP solver to facilitate external heuristics implemented in a procedural language which are consulted at specific points during the solving process via an API. HWASP could find solutions for all available instances of the Partner Units Problem (PUP) using a number of externally embedded heuristics.…”

Section: Domain-specific Heuristics In Asp: State Of the Artmentioning

confidence: 99%

Exploiting Partial Knowledge in Declarative Domain-Specific Heuristics for ASP

Taupe

Schekotihin

Schüller

et al. 2019

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Domain-specific heuristics are an important technique for solving combinatorial problems efficiently. We propose a novel semantics for declarative specifications of domain-specific heuristics in Answer Set Programming (ASP). Decision procedures that are based on a partial solution are a frequent ingredient of existing domain-specific heuristics, e.g., for placing an item that has not been placed yet in bin packing. Therefore, in our novel semantics negation as failure and aggregates in heuristic conditions are evaluated on a partial solver state. State-of-the-art solvers do not allow such a declarative specification. Our implementation in the lazy-grounding ASP system Alpha supports heuristic directives under this semantics. By that, we also provide the first implementation for incorporating declaratively specified domain-specific heuristics in a lazy-grounding setting. Experiments confirm that the combination of ASP solving with lazy grounding and our novel heuristics can be a vital ingredient for solving industrial-size problems.

show abstract

“…In this way a user can influence the search by resolving non-deterministic choices by means of conflicts. Another approach, implemented in hwasp [20], allows a user to define procedures replacing the native heuristics with custom ones. Using a specific data exchange interface the heuristic communicates with the solver and is invoked instead of the standard one if a non-deterministic choice has to be made.…”

Section: Tackling the Heuristics Challengementioning

confidence: 99%

Industrial Applications of Answer Set Programming

et al. 2018

View full text Add to dashboard Cite

Automated problem solving in combination with declarative specifications of search-problems have shown to substantially improve the implementation and maintenance costs as well as the man-machine interaction of deployed industrial applications. The knowledge representation and reasoning (KRR) framework of answer set programming (ASP) offers a rich representation language and high performance solvers. Therefore, ASP has become very attractive for the representation and solving of search-problems both for academia and industry. This article focuses on the latest industrial applications of ASP. We do not only present successful applications of ASP but also describe the development process and the design of ASP programs in an industrial context. Finally, we discuss current approaches to tackle the most significant application challenges such as grounding and runtime improvements by heuristics.

show abstract

Combining Answer Set Programming and domain heuristics for solving hard industrial problems (Application Paper)

Cited by 39 publications

References 31 publications

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Exploiting Partial Knowledge in Declarative Domain-Specific Heuristics for ASP

Industrial Applications of Answer Set Programming

Contact Info

Product

Resources

About