Efficient Minimal Model Generation Using Branching Lemmas

Hasegawa, Ryuzo; Fujita, Hiroshi; Koshimura, Miyuki

doi:10.1007/10721959_15

Cited by 13 publications

(7 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stable models that are subset-minimal with respect to a set of atoms have also been previously employed in the computation of paracoherent answer sets (Amendola et al 2017), and for circumscription (Alviano 2017a). Other strategies for the computation of minimal models have been previously proposed in early work (Niemelä 1996;Hasegawa et al 2000;Bry and Yahya 2000) preceding the invention of conflict-driven solvers; this limitation was overcome by Koshimura et al (2009). Going beyond the above, general approaches such as the algorithms for computing minimal sets over monotone predicates (MSMP; Janota and Marques-Silva 2016) could also be adapted for computing minimal models.…”

Section: Wasp-or Wasp-ict Wasp-opt Wasp-one Wasp-cm Claspmentioning

confidence: 99%

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

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: Wasp-or Wasp-ict Wasp-opt Wasp-one Wasp-cm Claspmentioning

confidence: 99%

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Alviano¹,

Dodaro²,

Järvisalo³

et al. 2018

Theory and Practice of Logic Programming

View full text Add to dashboard Cite

show abstract

“…The algorithms used for computing paracoherent answer sets are strictly related to the computation of minimal models of propositional theories. The first approaches to that problem (Niemelä 1996;Hasegawa, Fujita, and Koshimura 2000;Bry and Yahya 2000) were not able to take profit of modern learning-based algorithms (Koshimura et al 2009). Later the first algorithm able to overcome that technological limit for the computation of minimal models of SAT formulae was introduced in (Koshimura et al 2009) that is similar in principle to the MINIM algorithm; whereas the SPLIT algorithm is similar to the algorithms employed for computing cautious consequences of ASP programs (Alviano, Dodaro, and Ricca 2014) and backbones of SAT formulas (Janota, Lynce, and Marques-Silva 2015).…”

Section: Related Workmentioning

confidence: 99%

Externally Supported Models for Efficient Computation of Paracoherent Answer Sets

Amendola

Dodaro

Faber

et al. 2018

AAAI

View full text Add to dashboard Cite

Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning.While incoherence, the non-existence of answer sets for some programs, is an important feature of ASP, it has frequently been criticised and indeed has some disadvantages, especially for query answering.Paracoherent semantics have been suggested as a remedy, which extend the classical notion of answer sets to draw meaningful conclusions also from incoherent programs. In this paper we present an alternative characterization of the two major paracoherent semantics in terms of (extended) externally supported models. This definition uses a transformation of ASP programs that is more parsimonious than the classic epistemic transformation used in recent implementations.A performance comparison carried out on benchmarks from ASP competitions shows that the usage of the new transformation brings about performance improvements that are independent of the underlying algorithms.

show abstract

“…[16]). Later the attention shifted to the computation of minimal models of first-order clauses [29,23]. [29] proposed a tableaux-based method where candidate models are generated and then tested for minimality.…”

Section: Related Workmentioning

confidence: 99%

“…[29] proposed a tableaux-based method where candidate models are generated and then tested for minimality. [23] proposed a method able to reduce minimality tests on candidate models. The usage of hyperresolution for minimal models of first-order clauses was presented in [9] and implemented in Prolog.…”

Section: Related Workmentioning

confidence: 99%

Modular Paracoherent Answer Sets

Amendola

Eiter

Leone

2014

Logics in Artificial Intelligence

View full text Add to dashboard Cite

Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue, and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.

show abstract

Efficient Minimal Model Generation Using Branching Lemmas

Cited by 13 publications

References 7 publications

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Cautious reasoning in ASP via minimal models and unsatisfiable cores

Externally Supported Models for Efficient Computation of Paracoherent Answer Sets

Modular Paracoherent Answer Sets

Contact Info

Product

Resources

About