Anytime Computation of Cautious Consequences in Answer Set Programming

Alviano, Mario; Dodaro, Carmine; Ricca, Francesco

doi:10.1017/s1471068414000325

Cited by 22 publications

(22 citation statements)

References 32 publications

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“…The algorithm implemented in DLV is based on the enumeration of all stable models for computing their intersection. CLASP instead implements OR, and WASP implements both OR and ICT (Alviano et al 2014). An abstract framework of cautious reasoning, capturing the above-mentioned algorithms, has been presented by Brochenin and Maratea (2015).…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

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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).

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Section: Related Workmentioning

confidence: 99%

“…Otherwise, during the minimization, the computed stable model is used to improve the overestimation. Moreover, algorithm CM is also anytime by itself, since it is able to improve the underestimation during its computation, while algorithm MIN can be made anytime using the technique suggested by Alviano et al (2014).…”

Section: Related Workmentioning

confidence: 99%

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

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“…In fact, the detailed results provided in Tables 4 and 5 in the appendix yield excellent performance of ME-ASP on six Decision problems and of WASP+DLV on three Decision as well as three Query problems. The latter advantage is based on dedicated techniques for cautious reasoning (Alviano et al, 2014), while ME-ASP relies on stand-alone DLV for Query answering. Query problems also separate the first from the second group, consisting of WASP and LP2NORMAL+CLASP, where WASP applies the same cautious reasoning techniques as WASP+DLV to "unoptimized" instantiations at ground level and LP2NORMAL+CLASP provides no support at all.…”

Section: Results In the Sp Categorymentioning

confidence: 99%

“…The hybrid WASP+DLV system relies on GRINGO for grounding all but Query problems, where the latter are handled by means of DLV whose dedicated support for Query answering (Alviano, Faber, Greco, & Leone, 2012) allows WASP+DLV to compete in all domains. Unlike that, the WASP system exploits GRINGO also on Query problems, utilizing simple syntactic means along with Query answering functionalities at the ground level (Alviano, Dodaro, & Ricca, 2014), 2 which is still a drawback in data-driven domains (cf. Section 5).…”

Section: Wasp Teammentioning

confidence: 99%

The Sixth Answer Set Programming Competition

Gebser¹,

Maratea²,

Ricca³

2017

jair

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Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme, and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a "Marathon" track where the topperforming systems are given more time for solving hard benchmarks.

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“…Compared approaches. As a reference to the state of the art, we used CLASP v. 3.3.3 (Gebser et al 2012), which implements algorithm OR (i.e., over-approximation), and the best performing algorithms implemented by WASP (Alviano et al 2014;Alviano et al 2018), namely OR (i.e., over-approximation), ICT (i.e., under-approximation), OPT, and CM. Algorithm OPT was presented in (Alviano et al 2018).…”

Section: Experimental Analysismentioning

confidence: 99%

Abstract Solvers for Computing Cautious Consequences of ASP programs

Amendola¹,

Dodaro²,

Maratea³

2019

Theory and Practice of Logic Programming

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solvers are a method to formally analyze algorithms that have been profitably used for describing, comparing and composing solving techniques in various fields such as Propositional Satisfiability (SAT), Quantified SAT, Satisfiability Modulo Theories, Answer Set Programming (ASP), and Constraint ASP.In this paper, we design, implement and test novel abstract solutions for cautious reasoning tasks in ASP. We show how to improve the current abstract solvers for cautious reasoning in ASP with new techniques borrowed from backbone computation in SAT, in order to design new solving algorithms. By doing so, we also formally show that the algorithms for solving cautious reasoning tasks in ASP are strongly related to those for computing backbones of Boolean formulas. We implement some of the new solutions in the ASP solver WASP and show that their performance are comparable to state-of-the-art solutions on the benchmark problems from the past ASP Competitions. Under consideration for acceptance in TPLP. KEYWORDS:Answer Set Programming, Abstract solvers, Cautious reasoning solver, SUP (Lierler 2011); however, abstract solvers have been so far mainly applied to ASP solvers for brave reasoning tasks where, given an input query and a knowledge base expressed in ASP, answers are witnessed by ASP solutions, i.e., stable models (Baral 2003;Eiter et al. 1997;Gelfond and Lifschitz 1988;Gelfond and Lifschitz 1991;Marek and Truszczyński 1998;Niemelä 1999).However, in ASP, also cautious reasoning has been deeply studied in the literature: answers here must be witnessed by all stable models. This task has found a significant number of interesting applications as well, including consistent query answering (Arenas et al. 2003;Manna et al. 2013), data integration (Eiter 2005), multi-context systems (Brewka and Eiter 2007), and ontology-based reasoning (Eiter et al. 2008). Two well-known ASP solvers, i.e., DLV (Leone et al. 2006) and CLASP (Gebser et al. 2012), have been extended for computing cautious consequences of ASP programs. More recently, Alviano et al. (2014) presented a unified, high-level view of such solving procedures, and designed several algorithms for cautious reasoning in ASP, including those implemented in DLV and CLASP, borrowed from the backbone computation of Boolean formulas (Janota et al. 2015): all these techniques are implemented (and tested) on top of the ASP solver WASP (Alviano et al. 2015).In this paper we design, implement and test novel abstract solutions for cautious reasoning tasks in ASP. We show how to improve the current abstract solvers (Brochenin and Maratea 2015a) for cautious reasoning in ASP with further techniques borrowed from backbone computation in SAT, in order to design new solving algorithms. In particular, we import a technique called "chunk", which generalizes over-and under-approximation by testing a set soft atoms simultaneously for being added in the under-approximation, and core-based algorithms, which can be considered either a solution per se, or a way for pruning the set of atoms t...

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Anytime Computation of Cautious Consequences in Answer Set Programming

Cited by 22 publications

References 32 publications

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Cautious reasoning in ASP via minimal models and unsatisfiable cores

The Sixth Answer Set Programming Competition

Abstract Solvers for Computing Cautious Consequences of ASP programs

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