156,311 research outputs found
Data Provenance Inference in Logic Programming: Reducing Effort of Instance-driven Debugging
Data provenance allows scientists in different domains validating their models and algorithms to find out anomalies and unexpected behaviors. In previous works, we described on-the-fly interpretation of (Python) scripts to build workflow provenance graph automatically and then infer fine-grained provenance information based on the workflow provenance graph and the availability of data. To broaden the scope of our approach and demonstrate its viability, in this paper we extend it beyond procedural languages, to be used for purely declarative languages such as logic programming under the stable model semantics. For experiments and validation, we use the Answer Set Programming solver oClingo, which makes it possible to formulate and solve stream reasoning problems in a purely declarative fashion. We demonstrate how the benefits of the provenance inference over the explicit provenance still holds in a declarative setting, and we briefly discuss the potential impact for declarative programming, in particular for instance-driven debugging of the model in declarative problem solving
Correctness and completeness of logic programs
We discuss proving correctness and completeness of definite clause logic
programs. We propose a method for proving completeness, while for proving
correctness we employ a method which should be well known but is often
neglected. Also, we show how to prove completeness and correctness in the
presence of SLD-tree pruning, and point out that approximate specifications
simplify specifications and proofs.
We compare the proof methods to declarative diagnosis (algorithmic
debugging), showing that approximate specifications eliminate a major drawback
of the latter. We argue that our proof methods reflect natural declarative
thinking about programs, and that they can be used, formally or informally, in
every-day programming.Comment: 29 pages, 2 figures; with editorial modifications, small corrections
and extensions. arXiv admin note: text overlap with arXiv:1411.3015. Overlaps
explained in "Related Work" (p. 21
On the incorporation of interval-valued fuzzy sets into the Bousi-Prolog system: declarative semantics, implementation and applications
In this paper we analyse the benefits of incorporating interval-valued fuzzy
sets into the Bousi-Prolog system. A syntax, declarative semantics and im-
plementation for this extension is presented and formalised. We show, by using
potential applications, that fuzzy logic programming frameworks enhanced with
them can correctly work together with lexical resources and ontologies in order
to improve their capabilities for knowledge representation and reasoning
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