Relating constraint answer set programming languages and algorithms

Lierler, Yuliya

doi:10.1016/j.artint.2013.10.004

Cited by 46 publications

(47 citation statements)

References 13 publications

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Section: Introductionmentioning

confidence: 99%

“…In this way, the whole solving process amounts to a path in the graph. This concept proved successful for SAT [44], and also has been applied to several variants of Answer Set Programming [6,36,37].In this paper, we apply abstract solvers to certain problems in Dung's argumentation frameworks. In order to understand whether abstract solvers are well suited also for this domain, we consider quite advanced algorithms for solving problems that are hard for the second level of the polynomial hierarchy -the considered algorithms range from dedicated [45] to reduction-based [13,25] approaches (see [19] for a survey).…”

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Abstract solvers for Dung’s argumentation frameworks

Brochenin

Linsbichler

Maratea

et al. 2018

AAC

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TU Wien, Austria E-mails: linsbich@dbai.tuwien.ac.at, wallner@dbai.tuwien.ac.at, woltran@dbai.tuwien.ac.at Abstract. Abstract solvers are a quite recent method to uniformly describe algorithms in a rigorous formal way via graphs. Compared to traditional methods like pseudo-code descriptions, abstract solvers have several advantages. In particular, they provide a uniform formal representation that allows for precise comparisons of different algorithms. Recently, this new methodology has proven successful in declarative paradigms such as Propositional Satisfiability and Answer Set Programming. In this paper, we apply this machinery to Dung's abstract argumentation frameworks. We first provide descriptions of several advanced algorithms for the preferred semantics in terms of abstract solvers. We also show how it is possible to obtain new abstract solutions by "combining" concepts of existing algorithms by means of combining abstract solvers. Then, we implemented a new solving procedure based on our findings in CEGARTIX, and call it CEGARTIX+. We finally show that CEGARTIX+ is competitive and complementary in its performance to CEGARTIX on benchmarks of the first and second argumentation competition.Keywords: Abstract argumentation, abstract solvers IntroductionDung's concept of abstract argumentation [23] is nowadays a core formalism in Artificial Intelligence [4,46]. The problem of solving certain reasoning tasks on such frameworks is the centerpiece of many advanced higher-level argumentation systems. The problems to be solved can however be intractable and might even be hard for the second level of the polynomial hierarchy [24,26]. Thus, efficient and advanced algorithms have to be developed in order to deal with real-world size data within reasonable performance bounds. The argumentation community is currently facing this challenge [17] [44]. Hereby, one characterizes the possible states of computation as nodes of a graph, and the techniques (i.e., the computation steps in the algorithms) as arcs between nodes. In this way, the whole solving process amounts to a path in the graph. This concept proved successful for SAT [44], and also has been applied to several variants of Answer Set Programming [6,36,37].In this paper, we apply abstract solvers to certain problems in Dung's argumentation frameworks. In order to understand whether abstract solvers are well suited also for this domain, we consider quite advanced algorithms for solving problems that are hard for the second level of the polynomial hierarchy -the considered algorithms range from dedicated [45] to reduction-based [13,25] approaches (see [19] for a survey). We show that abstract solvers allow for convenient algorithms design resulting in a clear and mathematically precise description. Moreover, formal properties of the algorithms (i.e. correctness) are easily specified by means of related graph properties (i.e. reachability). We then illustrate how abstract solvers allow to highlight in a more clear way similarities and differences among solvin...

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Abstract solvers for Dung’s argumentation frameworks

Brochenin

Linsbichler

Maratea

et al. 2018

AAC

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“…Indeed, recall answer set (3). We note that the QAS Π ,p graph can be seen as a special case of the graph AC Π introduced in [18] for a more sophisticated class of programs called AC programs.…”

Section: The Transition Rule Query Propagate Followsmentioning

confidence: 99%

“…Constraint answer set programming (CASP) [18] is one of the directions of research that has been largely motivated by an attempt to solve the problem. It integrates answer set programming with constraint (logic) programming, which allows applying constraint processing techniques for effective reasoning over non-boolean constructs.…”

Section: Introductionmentioning

confidence: 99%

Prolog and ASP Inference under One Roof

Balduccini

Lierler

Schüller

2013

Logic Programming and Nonmonotonic Reasoning

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Abstract. Answer set programming (ASP) is a declarative programming paradigm stemming from logic programming that has been successfully applied in various domains. Despite amazing advancements in ASP solving, many applications still pose a challenge that is commonly referred to as grounding bottleneck. Devising, implementing, and evaluating a method that alleviates this problem for certain application domains is the focus of this paper. The proposed method is based on combining backtracking-based search algorithms employed in answer set solvers with SLDNF resolution from PROLOG. Using PROLOG inference on non-ground portions of a given program, both grounding time and the size of the ground program can be substantially reduced.

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“…A high level view of the languages and solving techniques employed by these solvers can be found in (Lierler 2014). There, by relying on the framework of abstract solvers, i.e., a graph-based representation of solving algorithms, similarities and differences among these solvers are formally stated by means of comparison of the related graphs.…”

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confidence: 99%

CASP solutions for planning in hybrid domains

Balduccini

Magazzeni

Maratea

et al. 2017

Theory and Practice of Logic Programming

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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.

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Relating constraint answer set programming languages and algorithms

Cited by 46 publications

References 13 publications

Abstract solvers for Dung’s argumentation frameworks

Abstract solvers for Dung’s argumentation frameworks

Prolog and ASP Inference under One Roof

CASP solutions for planning in hybrid domains

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