Assumptions of problem-solving methods

Benjamins, V. Richard; Pierret-Golbreich, Christine

doi:10.1007/3-540-61273-4_1

Cited by 32 publications

(13 citation statements)

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“…Guidelines for library design according to this principle are discussed in ( [116], [115]). In a library organised according to the taskmethod principle, PSMs are indexed, based on two factors: (1) on the competence of the PSMs -which specifies what a PSM can achieve [8], and (2) on their assumptions -which specify the assumptions under which the PSM can be applied correctly, such as its requirements on domain knowledge ( [17], [18]). Selection of PSMs from such libraries first considers the competence of PSMs (selecting those whose competences match the task at hand), and then the assumptions of PSMs (selecting those whose assumptions are satisfied).…”

Section: Organisation Of Librariesmentioning

confidence: 99%

“…a certain PSM needs a causal domain model) or to task knowledge (a certain PSM generates locally optimal solutions). To our knowledge, there does not exist a library organised following this principle, but work is currently being performed to shed more light on the role of assumptions in libraries for knowledge engineering ( [17], [18], [56], [58]). …”

Section: Organisation Of Librariesmentioning

confidence: 99%

“…In this way, these ontologies help to solve the 'interaction problem' [33], which states that domain knowledge cannot be independently represented from how it will be used in problem solving, and vice versa. Method and task ontologies enable to make explicit the interaction between problem-solving and domain knowledge through assumptions ( [17], [60], [18]). …”

Section: Types Of Ontologiesmentioning

confidence: 99%

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Knowledge engineering: Principles and methods

Studer

Benjamins

Fensel

1998

Data & Knowledge Engineering

2,735

1,008

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This paper gives an overview about the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in the last years we describe three modeling frameworks: CommonKADS, MIKE, and PROTÉGÉ-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods, and ontologies. We conclude with outlining the relationship of Knowledge Engineering to Software Engineering, Information Integration and Knowledge Management. Key WordsKnowledge Engineering, Knowledge Acquisition, Problem-Solving Method, Ontology, Information Integration IntroductionIn earlier days research in Artificial Intelligence (AI) was focused on the development of 2 formalisms, inference mechanisms and tools to operationalize Knowledge-based Systems (KBS). Typically, the development efforts were restricted to the realization of small KBSs in order to study the feasibility of the different approaches.Though these studies offered rather promising results, the transfer of this technology into commercial use in order to build large KBSs failed in many cases. The situation was directly comparable to a similar situation in the construction of traditional software systems, called "software crisis" in the late sixties: the means to develop small academic prototypes did not scale up to the design and maintenance of large, long living commercial systems. In the same way as the software crisis resulted in the establishment of the discipline Software Engineering the unsatisfactory situation in constructing KBSs made clear the need for more methodological approaches.So the goal of the new discipline Knowledge Engineering (KE) is similar to that of Software Engineering: turning the process of constructing KBSs from an art into an engineering discipline. This requires the analysis of the building and maintenance process itself and the development of appropriate methods, languages, and tools specialized for developing KBSs.Subsequently, we will first give an overview of some important historical developments in KE: special emphasis will be put on the paradigm shift from the so-called transfer approach to the so-called modeling approach. This paradigm shift is sometimes also considered as the transfer from first generation expert systems to second generation expert systems [43]. Based on this discussion Section 2 will be concluded by describing two prominent developments in the late eighties: Role-limiting Methods [99] and Generic Tasks [36]. In Section 3 we will present some modeling frameworks which have been developed in recent years:, and PROTÈGÈ-II [123]. Section 4 gives a short overview of specification languages for KBSs. Problem-solving methods have been a major research ...

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Section: Organisation Of Librariesmentioning

confidence: 99%

Section: Organisation Of Librariesmentioning

confidence: 99%

Section: Types Of Ontologiesmentioning

confidence: 99%

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Knowledge engineering: Principles and methods

Studer

Benjamins

Fensel

1998

Data & Knowledge Engineering

2,735

1,008

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“…For a number of these problem types, libraries of PSMs that solve the problem type have been proposed. These libraries allow, on the basis of suitability criteria or assumptions, that the knowledge engineer configures a problem-solving model that accurately describes the knowledge-intensive task at hand (Benjamins, Fensel & Straatman, 1996;Benjamins & Pierret-Golbreich, 1996;.…”

Section: Using Libraries Of Psms In Industrial Applicationsmentioning

confidence: 99%

Preserving conceptual structures in design and implementation of industrial KBSs

Speel¹,

Aben²

1998

International Journal of Human-Computer Studies

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“…First, availability assumptions (Benjamins & Pierret-Golbreich, 1996) require the availability of a certain type of knowledge to operate. In terms of the library developed here, this means that knowledge must be available to fill a certain static role.…”

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confidence: 99%