Showing papers by "Peter Baumgartner published in 1997"

Semantically Guided Theorem Proving for Diagnosis Applications.

Abstract: In this paper we demonstrate how general purpose automated theorem proving techniques can be used to solve realistic model-based diagnosis problems For this we modify a model generating tableau calculus such that a model of a correctly behaving device can be used to guide the search for minimal diagnoses Our experiments show that our general approach is competitive with specialized diagnosis systems

A rational and efficient algorithm for view deletion in databases

Abstract: In this paper, we show how techniques from disjunctive logic program ming and classical first-order theorem proving can be used for efficient (deductive) database updates. The key idea is to tranform the given database together with the update request into a disjunctive logic program and apply disjunctive techniques (such as minimal model reasoning) to solve the o riginal update problem. We present two variants of our algorithm both of wh ich are of polynomial space complexity. One variant, which is based on offlin e preprocessing, is of polynomial time complexity. We also show that b oth variants are rational in the sense that they satisfy certain rationality po s ulates stemming from philosophical works on belief dynamics.

Tableaux for Diagnosis Applications

Abstract: In [NF96] a very efficient system for solving diagnosis tasks has been described, which is based on belief revision procedures and uses first order logic system descriptions. In this paper we demonstrate how such a system can be rigorously formalized from the viewpoint of deduction by using the calculus of hyper tableaux [BFN96]. The benefits of this approach are twofold: first, it gives us a clear logical description of the diagnosis task to be solved; second, as our experiments show, the approach is feasible in practice and thus serves as an example of a successful application of deduction techniques to real-world applications.

Calculi for Disjunctive Logic Programming.

Abstract: In this paper we investigate relationships between top-down and bottomup approaches to computation with disjunctive logic programs (DLPs). The bottom-up calculus considered, hyper tableaux, is depicted in its ground version and its relation to fixed point approaches from the literature is investigated. For the top-down calculus we use restart model elimination (RME) and show as our main result that hyper tableaux provide a bottom-up semantics for it. This generalizes the well-known result linking the T -operator to SLDresolution for definite programs towards disjunctive programs. Furthermore we discuss that hyper tableaux can be seen as an extension of SLO-resolution.

Calculi for disjunctive logic programming

Abstract: In this paper we investigate relationships between top-down and bottomup approaches to computation with disjunctive logic programs (DLPs). The bottom-up calculus considered, hyper tableaux, is depicted in its ground version and its relation to fixed point approaches from the literature is investigated. For the top-down calculus we use restart model elimination (RME) and show as our main result that hyper tableaux provide a bottom-up semantics for it. This generalizes the well-known result linking the T -operator to SLDresolution for definite programs towards disjunctive programs. Furthermore we discuss that hyper tableaux can be seen as an extension of SLO-resolution.

A Disjunctive Positive Refinement of Model Elimination and its Application to Subsumption Deletion

Abstract: The Model Elimination (ME) calculus is a refutationally complete, goal-oriented calculus for first-order clause logic. In this article, we introduce a new variant called disjunctive positive ME (DPME); it improves on Plaisted’s positive refinement of ME in that reduction steps are allowed only with positive literals stemming from clauses having at least two positive literals (so-called disjunctive clauses). DPME is motivated by its application to various kinds of subsumption deletion: in order to apply subsumption deletion in ME equally successful as in resolution, it is crucial to employ a version of ME that minimizes ancestor context (i.e., the necessary A-literals to find a refutation). DPME meets this demand. We describe several variants of ME with subsumption, the most important ones being ME with backward and forward subsumption and the Ta-Context Check. We compare their pruning power, also taking into consideration the well-known regularity restriction. All proofs are supplied. The practicability of our approach is demonstrated with experiments.