The Intelligent Grounder of DLV

Faber, Wolfgang; Leone, Nicola; Perri, Simona

doi:10.1007/978-3-642-30743-0_17

Cited by 25 publications

(27 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…consists of all ground instances of atom a that belong to every answer set of P . Taking the prerequisites of instantiation procedures like "intelligent grounding" (Faber, Leone, & Perri, 2012) into account, non-ground ASP-Core-2 programs have to comply with additional requirements (Calimeri et al, 2012), including in particular finiteness of answer sets and safety. In a nutshell, these conditions require the availability of (positive) occurrences of variables within the bodies of rules as well as aggregate or choice elements in order to restrict the relevant substitutions and enable grounders to compute a (finite) ground program, which is typically much smaller yet equivalent to grnd(P ).…”

Section: Semanticsmentioning

confidence: 99%

“…For instance, adding arc(X, Y ) to the body establishes this condition for rule (4).) Unlike that, the DLV grounder (Leone, Pfeifer, Faber, Eiter, Gottlob, Perri, & Scarcello, 2006;Faber et al, 2012) and recent versions of GRINGO (Gebser, Kaminski, König, & Schaub, 2011a; are based on semi-naive bottom-up evaluation (cf. Abiteboul, Hull, & Vianu, 1995), only requiring safety, i.e., some occurrence in a positive precondition for each variable, to iteratively generate ground instances of recursive rules until no new head atoms are produced anymore.…”

Section: Evaluation Processmentioning

confidence: 99%

See 1 more Smart Citation

The Sixth Answer Set Programming Competition

Gebser¹,

Maratea²,

Ricca³

2017

jair

View full text Add to dashboard Cite

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.

show abstract

Section: Semanticsmentioning

confidence: 99%

Section: Evaluation Processmentioning

confidence: 99%

The Sixth Answer Set Programming Competition

Gebser¹,

Maratea²,

Ricca³

2017

jair

View full text Add to dashboard Cite

show abstract

“…Hence, the rule instantiation is mainly directed by the instantiated atoms already present in the sets IN and M BT . The algorithm used in the ASPeRiX solver and described below is inspired by the previous work realized on the DLV grounder (Faber et al 2012;Perri et al 2007) which is based on the semi-naive evaluation technique of (Ullman 1989). The goal is to find a substitution for all the literals of the body of a rule r thanks to the atoms already in IN , M BT or OU T .…”

Section: Rule Instantiationmentioning

confidence: 99%

“…ASP grounders Lparse (Syrjänen 1998) and versions up to 3.0 of Gringo (Gebser et al 2007) accept programs respecting some syntactic domain restrictions and are able to deal with some restricted versions of functions. DLV grounder (Faber et al 2012) and Gringo (since version 3.0) (Gebser et al 2011) only require programs to be safe and can deal with all programs having a finite instantiation. DLV guarantees finite instantiation for finitely ground programs but membership in this class is not decidable.…”

Section: Asperix Languagementioning

confidence: 99%

`ASPeRiX`, a first-order forward chaining approach for answer set computing

Lefèvre¹,

Béatrix²,

Stéphan³

et al. 2017

Theory and Practice of Logic Programming

View full text Add to dashboard Cite

The natural way to use Answer Set Programming (ASP) to represent knowledge in Artificial Intelligence or to solve a combinatorial problem is to elaborate a first order logic program with default negation. In a preliminary step this program with variables is translated in an equivalent propositional one by a first tool: the grounder. Then, the propositional program is given to a second tool: the solver. This last one computes (if they exist) one or many answer sets (stable models) of the program, each answer set encoding one solution of the initial problem. Until today, almost all ASP systems apply this two steps computation.In this article, the project ASPeRiX is presented as a first order forward chaining approach for Answer Set Computing. This project was amongst the first to introduce an approach of answer set computing that escapes the preliminary phase of rule instantiation by integrating it in the search process. The methodology applies a forward chaining of first order rules that are grounded on the fly by means of previously produced atoms. Theoretical foundations of the approach are presented, the main algorithms of the ASP solver ASPeRiX are detailed and some experiments and comparisons with existing systems are provided.

show abstract

“…However, for non-ground formulae the complexity result from Theorem 4.14 does not hold, because transformation into a boolean sat problem is then exponential in the number of possible groundings. Finding a sound thread then requires the use of sophisticated grounding procedures, (e.g., Dal Palù, Dovier, Pontelli, &Rossi, 2009 andFaber, Leone, &Perri, 2012), which is beyond the scope of this work.…”

Section: Constraining Possible Worlds At Individual Time Pointsmentioning

confidence: 99%

PDT Logic: A Probabilistic Doxastic Temporal Logic for Reasoning about Beliefs in Multi-agent Systems

Martiny¹,

Möller²

2016

jair

View full text Add to dashboard Cite

We present Probabilistic Doxastic Temporal (PDT) Logic, a formalism to represent and reason about probabilistic beliefs and their temporal evolution in multi-agent systems. This formalism enables the quantification of agents' beliefs through probability intervals and incorporates an explicit notion of time. We discuss how over time agents dynamically change their beliefs in facts, temporal rules, and other agents' beliefs with respect to any new information they receive. We introduce an appropriate formal semantics for PDT Logic and show that it is decidable. Alternative options of specifying problems in PDT Logic are possible. For these problem specifications, we develop different satisfiability checking algorithms and provide complexity results for the respective decision problems. The use of probability intervals enables a formal representation of probabilistic knowledge without enforcing (possibly incorrect) exact probability values. By incorporating an explicit notion of time, PDT Logic provides enriched possibilities to represent and reason about temporal relations.

show abstract

The Intelligent Grounder of DLV

Cited by 25 publications

References 34 publications

The Sixth Answer Set Programming Competition

The Sixth Answer Set Programming Competition

`ASPeRiX`, a first-order forward chaining approach for answer set computing

PDT Logic: A Probabilistic Doxastic Temporal Logic for Reasoning about Beliefs in Multi-agent Systems

Contact Info

Product

Resources

About

The Intelligent Grounder of DLV

Cited by 25 publications

References 34 publications

The Sixth Answer Set Programming Competition

The Sixth Answer Set Programming Competition

ASPeRiX, a first-order forward chaining approach for answer set computing

PDT Logic: A Probabilistic Doxastic Temporal Logic for Reasoning about Beliefs in Multi-agent Systems

Contact Info

Product

Resources

About

`ASPeRiX`, a first-order forward chaining approach for answer set computing