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Logic Programming and Knowledge Representation LPKR 97


Logic Programming and Knowledge Representation LPKR 97

Danford's Inn, Port Jefferson, Long Island, Oct. 16

Gerd Brewka

This ILPS'97 postconference workshop was the third in a series organized by J. Dix, L.M. Pereira and T. Przymusinski since 1994. It is obvious that intelligent machines need tremendous amounts of knowledge for solving difficult tasks like diagnosis, planning, configuration, decision support and many others. Logic programming's declarative nature as well as its amenability to implementation make it a very good candidate for knowledge representation purposes.

The papers presented this year's workshop were centered around four major topics: updates, abduction, priorities, and semantics.

Updates, that is program modifications reflecting changes in the actual world, have received considerable interest in the logic programming community within the last few years. In particular, specifications of updates through so-called update programs have been investigated. The paper presented by J. Leite and L.M. Pereira shows that in order to model update in a logic programming context adequately it is often insufficient just to take the models of programs into account. The program rules themselves give additional information about why a certain belief is accepted, e.g. because of a causal relationship. Consequently, updates should be conceived as program transformations, not as operations on models. The authors describe how such transformations can be defined both for normal and for extended logic programs.

The paper by A. Yahya (which was actually presented by D. Seipel) investigates the issue of adding a clause to, respectively deleting it from, a disjunctive deductive database. Several possibilities for accomplishing this in different classes of theories are presented. In each case minimality of change is measured in terms of its effect on the minimal model structure of the theory.

Two presentations were given in the abductive logic programming session. R. Li, L.M. Pereira and V. Dahl showed how the framework of abductive logic programming can be used to model the incorporation of test results into incomplete action domain descriptions. The approach leads to a stepwise refinement of descriptions in a high level action language and solves a problem suggested by V. Lifschitz.

A system for learning abductive logic programs was presented by E. Lamma, M. Milano and F. Riguzzi. The underlying algorithm is based on a top-down algorithm which takes into account abducibles and integrity constraints. Instead of the standard deductive proof procedure abductive inference is used to establish coverage of positive and negative examples in the learning process.

In the priority section I myself presented a new approach to preference handling in extended logic programs under answer set semantics. A given preference relation on program rules is extended to a preference relation on answer sets, and the meaning of a prioritized program is determined through its most preferred answer sets. The approach is based on a program reduction which is dual to the standard Gelfond/Lifschitz reduction. It provably satisfies reasonable principles for preference handling in rule based systems.

Instead of modifying the semantics, M. Gelfond and T.C. Son proposed to use a certain set of domain independent axioms describing declaratively how conclusions are to be drawn from defeasible rules with additional preference information. To make this possible the original rules are reified and a number of meta-predicates (like holds_by_default, may_hold, defeated etc.) are introduced. The authors demonstrated that the standard examples from the literature can be handled adequately this way.

The last and biggest session on semantics contained four presentations. H. Decker developed a three- valued semantics for integrity constraints based on the notion of a sustained model. Existing two-valued semantics for integrity constraints turn out to be biased either towards satisfaction or towards violation of constraints. Using a three-valued semantics such problems can be avoided.

In the paper by S. Greco, N. Leone and F. Scarcello disjunctive datalog is extended by nested rules, i.e. rules whose heads can be composed of rules. The authors argue that this extension leads to more natural formulations of complex reasoning problems. They presented a semantics for their extension and discussed its complexity.

D. Seipel introduced so-called partial evidential stable models and showed that such models always exist for disjunctive deductive databases. These models are a subset of the minimal models, they coincide with partial stable models whenever the latter exist. The definition of partial evidential stable models is based on a preference relation which captures the idea of minimizing reasoning by contradiction.

Finally, an introspective logic of belief was presented by L.-Y. Yuan and J.-H. You. The logic is a modal logic extended by a new negative introspection rule. It turns out that this new logic is able to characterize almost all nonmonotonic semantics. The authors also argue that their logic has considerable advantages when it comes to implementation.

In conclusion, this year's workshop - as the two workshops held in 94 and 96 - demonstrated important progress in the field. Although semantical issues still play an important role in the discussion, more and more solutions for hard knowledge representation problems based on logic programming technology seem to be emerging. I take this as a clear indication that investigations of the kind discussed at the workshop are on the right track.

Gerhard Brewka,

Universitaet Leipzig

Institut fuer Informatik Augustusplatz 10/11 04109 Leipzig Germany


Coordinator's Report ] [ Logic Programming and Knowledge Representation LPKR 97 ] Aplications of Natural Language to Information Systems ] DYNAMICS97 (Trans)Actions and Change in Logic Programming and Deductive Databases ] LPNMR '97 ] Internet Library of Logic Programming Systems and Test Cases ]

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