Nicolaas Mars

Ontology-Based Geographic Data Set Integration

In order to develop a system to propagate updates we investigate the semantic and spatial relationships between independently produced geographic data sets of the same region (data set integration). The goal of this system is to reduce operator intervention in update operations between corresponding (semantically similar) geographic object instances. Crucial for this reduction is certainty about the semantic similarity of different object representations. In this paper we explore a framework for ontology-based geographic data set integration, an ontology being a collection of shared concepts. Components of this formal approach are an ontology for topographic mapping (a domain ontology), an ontology for every geographic data set involved (the application ontologies), and abstraction rules (or capture criteria). Abstraction rules define at the class level the relationships between domain ontology and application ontology. Using these relationships, it is possible to locate semantic similarity at the object instance level with methods from computational geometry (like overlay operations). The components of the framework are formalized in the Prolog language, illustrated with a fictitious example, and tested on a practical example.

Introduction to TIPS: a theory for creative design

A highly intriguing problem in combining artificial intelligence and engineering design is automation of the creative and innovative phases of the design process. This paper gives a brief introduction to the theory of inventive problem solving (TIPS) selected as a theoretical basis of the authors research efforts in this field. The research is conducted in the Stevin Project of the Knowledge-Based System Group of the University of Twente (Enschede, The Netherlands) in cooperation with the Invention Machine Laboratory (Minsk, Belarus). This collaboration aims at developing a formal basis for the creation of an automated reasoning system to support creative engineering design.

Issues in practical model-based diagnosis

The model-based diagnosis project at the University of Twente has been directed at improving the practical usefulness of model-based diagnosis. In cooperation with industrial partners, the research addressed the modeling problem and the efficiency problem in model-based reasoning. n nMain results of this research are that (1) re-use of electronically available descriptions of systems for diagnostic purposes is possible, and (2) efficient reasoning can be realized using PDE, hierarchic models, and a simple diagnostic strategy. We have built a prototype diagnostic system which shows the technical feasibility of model-based diagnosis in a computer system. n nThe project was concluded in July 1993 by the development of the `Diagnostic Toolbox?. The Diagnostic Toolbox supports the modeling of technical systems for diagnostic purposes, and it contains several model-based reasoning methods.

A knowledge-based approach to VLSI-design in an open CAD-environment

A knowledge-based approach is suggested to assist a designer in the increasingly complex task of generating VLSI-chips from abstract, high-level specifications of the system. The complexity of designing VLSI-circuits has reached a level where computer-based assistance has become indispensable. Not all of the design tasks allow for algorithmic solutions. AI technique can be used, in order to support the designer with computer-aided tools for tasks not suited for algorithmic approaches. The approach described in this paper is based upon the underlying characteristics of VLSI design processes in general, comprising all stages of the design. A universal model is presented, accompanied with a recording method for the acquisition of design knowledge - strategic and task-specific - in terms of the design actions involved and their effects on the design itself. This method is illustrated by a simple design example: the implementation of the logical EXOR-component. Finally suggestions are made for obtaining a universally usable architecture of a knowledge-based system for VLSI-design.

Comparison of implemented ontologies

A number of groups developing knowledge-based systems have found (or at least posited) that the design and representation of a limitative set of concepts and relations, a so-called ontology, can contribute to sharing and reusing knowledge bases. However, very few descriptions of implemented ontologies have appeared in the literature. No comparison of competing proposals is available, let alone an empirical determination of the benefits of using an ontology. There is no accepted method for designing and building such ontologies, nor is it clear how ontologies can best be evaluated.

Reusing design information for model-based diagnosis

Model-based diagnosis (MBD) is a technique to locate faults in a system with the aid of a model of that system. The model describes the correct behavior of the system, and possibly also the behavior in case of a fault. In the field of model-based diagnosis, most attention has been given to the problem of reasoning: how to derive diagnoses, given a model. When applying MBD in practice, modeling appears to be a problem of equal magnitude. In this paper, we analyze the modeling process, and show how design information can be used in this process. We investigated the use of information in two standard languages for information interchange: EDIF and VHDL. We expect that the results from this research carry over to other design formats.