A logical basis for object oriented programming

Laenens, Els; Vermeir, Dirk

doi:10.1007/bfb0018450

Cited by 5 publications

(5 citation statements)

References 12 publications

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“…Note that such priority is not based on inheritance (which is tailored for "flat" objects). Therefore, inheritance-based approaches such as those by Laenens and Vermeir (1990) or Buccafurri et al (1996) do not apply here. Furthermore, implicit priorities derived from context information as above must be combined with explicit user preferences from the selection policy, and arising conflicts must be resolved.…”

Section: Examplementioning

confidence: 99%

A knowledge-based approach for selecting information sources

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Tompits

2007

Theory and Practice of Logic Programming

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Through the Internet and the World-Wide Web, a vast number of information sources has become available, which offer information on various subjects by different providers, often in heterogeneous formats. This calls for tools and methods for building an advanced information-processing infrastructure. One issue in this area is the selection of suitable information sources in query answering. In this paper, we present a knowledge-based approach to this problem, in the setting where one among a set of information sources (prototypically, data repositories) should be selected for evaluating a user query. We use extended logic programs (ELPs) to represent rich descriptions of the information sources, an underlying domain theory, and user queries in a formal query language (here, XML-QL, but other languages can be handled as well). Moreover, we use ELPs for declarative query analysis and generation of a query description. Central to our approach are declarative source-selection programs, for which we define syntax and semantics. Due to the structured nature of the considered data items, the semantics of such programs must carefully respect implicit context information in source-selection rules, and furthermore combine it with possible user preferences. A prototype implementation of our approach has been realized exploiting the DLV KR system and its plp front-end for prioritized ELPs. We describe a representative example involving specific movie databases, and report about experimental results.

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Section: Examplementioning

confidence: 99%

A knowledge-based approach for selecting information sources

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Fink

Tompits

2007

Theory and Practice of Logic Programming

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“…In Section 4.3 we elaborate on the simulation of consistency-restoring rules (Balduccini and Gelfond 2003) using the preferred answer set semantics. In Section 4.4, we compare our semantics with DOL (Buccafurri et al 1998), DLP < (Buccafurri et al 1999) and ordered logic (Laenens and Vermeir 1990). Section 5 illustrates another application of the preferred answer set semantics: the minimal repairs of a database D w.r.t.…”

Section: Examplementioning

confidence: 99%

“…Ordered logic programming has a long history: in (Laenens and Vermeir 1990;Gabbay et al 1991;Laenens and Vermeir 1992) semantics are given for ordered programs containing non-disjunctive rules, while (Buccafurri et al 1998;Buccafurri et al 1999) apply the same ideas to the disjunctive case.…”

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confidence: 99%

“…This difference in using the order relation has important consequences on the complexity of the resulting formalisms: while the semantics that use the order in a "local" way all stay in the same complexity class of the underlying non-ordered language, i.e. Σ P 1 -complete for (Laenens and Vermeir 1990;Gabbay et al 1991;Laenens and Vermeir 1992) and Σ P 2 -complete for (Buccafurri et al 1998;Buccafurri et al 1999), the "global order" semantics from Section 3 increments the complexity in the polynomial hierarchy, i.e. Σ P 2 -complete instead of Σ P 1 -complete (see Section 3.2).…”

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confidence: 99%

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Preferred answer sets for ordered logic programs

Nieuwenborgh

Vermeir

2006

Theory and Practice of Logic Programming

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We extend answer set semantics to deal with inconsistent programs (containing classical negation), by finding a "best" answer set. Within the context of inconsistent programs, it is natural to have a partial order on rules, representing a preference for satisfying certain rules, possibly at the cost of violating less important ones. We show that such a rule order induces a natural order on extended answer sets, the minimal elements of which we call preferred answer sets. We characterize the expressiveness of the resulting semantics and show that it can simulate negation as failure, disjunction and some other formalisms such as logic programs with ordered disjunction. The approach is shown to be useful in several application areas, e.g. repairing database, where minimal repairs correspond to preferred answer sets.

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“…Equipping logic programs with a preference relation on the rules has a relatively long history [21,20,18,9,7,5,32,1,29]. Also approaches that consider a preference relation on (extended) literals have been considered: [26] proposes explicit preferences while [4,6] encodes dynamic preferences within the program.…”

Section: Conclusion and Directions For Further Researchmentioning

confidence: 99%

On Programs with Linearly Ordered Multiple Preferences

2004

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Abstract. The extended answer set semantics for logic programs allows for the defeat of rules to resolve contradictions. We propose a refinement of these semantics based on a preference relation on extended literals. This relation, a strict partial order, induces a partial order on extended answer sets. The preferred answer sets, i.e. those that are minimal w.r.t. the induced order, represent the solutions that best comply with the stated preference on extended literals. In a further extension, we propose linearly ordered programs that are equipped with a linear hierarchy of preference relations. The resulting formalism is rather expressive and essentially covers the polynomial hierarchy. E.g. the membership problem for a program with a hierarchy of height n is Σ P n+1 -complete. We illustrate an application of the approach by showing how it can easily express hierarchically structured weak constraints, i.e. a layering of "desirable" constraints, such that one tries to minimize the set of violated constraints on lower levels, regardless of the violation of constraints on higher levels.

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A logical basis for object oriented programming

Cited by 5 publications

References 12 publications

A knowledge-based approach for selecting information sources

A knowledge-based approach for selecting information sources

Preferred answer sets for ordered logic programs

On Programs with Linearly Ordered Multiple Preferences

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