Models, methods, roles and tasks: Many labels—one idea?

Karbach, Werner; Linster, Marc; Voß, Angi

doi:10.1016/s1042-8143(05)80011-1

Cited by 34 publications

(8 citation statements)

References 18 publications

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“…One of the indicators of this fact is the existence of commonly agreed terminology between the various research groups in the field. Over the past years, there has been terminological confusion and debate between the different groups (Karbach, Linster & Voss, 1990). However, during KAW'96 this was not an issue anymore.…”

Section: Motivation For This Special Issuementioning

confidence: 99%

Editorial: problem-solving methods

Benjamins¹,

Fensel²

1998

International Journal of Human-Computer Studies

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Section: Motivation For This Special Issuementioning

confidence: 99%

Editorial: problem-solving methods

Benjamins¹,

Fensel²

1998

International Journal of Human-Computer Studies

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“…An early attempt to survey and classify most approaches in knowledge acquisition was given by [Boo88]. Methodologically close in spirit to this work are [KLV90], [NPB+91], [Lin93], and [FeH94]. [KLV90] survey four approaches to model-based knowledge acquisition and extract three common hypotheses which are now common places in knowledge acquisition.…”

Section: Introductionmentioning

confidence: 95%

“…Methodologically close in spirit to this work are [KLV90], [NPB+91], [Lin93], and [FeH94]. [KLV90] survey four approaches to model-based knowledge acquisition and extract three common hypotheses which are now common places in knowledge acquisition. [NPB+91] tries to give a complete classification on knowledge acquisition and [Lin93] focuses on solutions of the Sisyphus-I problem.…”

Section: Introductionmentioning

confidence: 99%

A comparison of two approaches to model-based knowledge acquisition

Fensel¹,

Poeck

1994

Lecture Notes in Computer Science

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Abstract. This paper discusses and compares two different approaches to model-based knowledge acquisition. That is, we regard the Model-based and Incremental Knowledge Engineering (MIKE) approach and the Configurable Role-limiting Method approach (CRLM). MIKE is based on the distinction of different phases in the software development process. It uses the formal and operational knowledge specification language KARL allowing a precise and unique description of a model of expertise which is the outcome of the analysis phase. CRLM is based on the rolelimiting method approach. Role limiting shells are implementations of strong problem-solving methods and substantially simplify knowledge acquisition through guidance by predefined models of problem-solving and by sophisticated graphical user interfaces. The main disadvantages, namely inflexibility and brittleness, are to some degree overcome by the CRLM where the shell's problem-solving methods are split into smaller parts, which can then be reconfigured allowing the integration of new methods or other method combinations. Although these two approaches are often discussed as contradictory, we, however, experienced that both approaches complete each other very well. As an outcome of our comparison, we outline topics of future research for both approaches.

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“…The study of different problem classes is important in research on knowledge acquisition, as proved by Clancey's work on a typology of problem classes [16], or KADS interpretation model library [11] or the generic task approach [15] or research on problem solving methods [36,32]. Topoi seem to be often used in some problem classes: our analysis of the different problem classes for which KADS offers an interpretation model confirms the usefulness of topoi for diagnosis by causal tracing, for monitoring, for behaviour prediction and for design.…”

Section: Synthesis Tasksmentioning

confidence: 99%

Acquisition of gradual knowledge

Dieng

Corby

Lapalut

1993

Knowledge Acquisition for Knowledge-Based Systems

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Abstract. Topoi are gradual inference rules, often used by experts in several problem classes: they can be exploited at various phases of a knowledge-based system life cycle. They can be studied at the two levels distinguished by Newelh the knowledge level and the symbol level. Some knowledge elicitation techniques such as rating grids and some knowledge acquisition methods such as KADS and KOD can be exploited in order to facilitate the acquisition of topoi. At the symbol level, different representations and implementations of topoi can be proposed and topoi can be formalized through several qualitative physics formalisms. IntroductionThe notion of topoi 1 stems from Anscombre and Ducrot's argumentation theory [2]. A topos is a gradual inference rule such as "The more P, the more Q", "The less P, the less Q", ~'The more P, the less Q" or "The less P, the more Q", where P and Q are properties. The first two topoi are called positive topoi and the last two negative topoi. Several researchers studied the interest of such gradual knowledge for argumentation in linguistics [12,41] and for artificial intelligence: in particular, in the framework of knowledge-based systems (KBS), some researchers studied thoroughly the use of topoi for knowledge acquisition [23,27] Let us give a brief description of such research. In [12,41], the authors propose a topoi-based theory of argumentation in natural language. Topoi are seen as gradual rules that are applied to some elements of the signification of a phrase, and help to determine the argumentative orientation of the concerned utterance. A speaker chooses the topoi he supposes shared by his interlocutors. Topoi play an important role for representing expertise. In [41], the author distinguishes descriptive topoi and heuristic topoi and exploits the notion of topoi for explanations of an expert system. In [40], the author relies on the possibility theory and on fuzzy sets in order to reason on gradual rules. The dynamic gradual behaviour of a KBS is represented through a topoi base in [18]. The notion of conditional topoi is introduced in order to avoid conflicts between apparently contradictory topoi. The topoi base is exploited for specification and validation 1 The term "topoi" was chosen as a tribute to Aristotle's topoi.

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Models, methods, roles and tasks: Many labels—one idea?

Cited by 34 publications

References 18 publications

Editorial: problem-solving methods

Editorial: problem-solving methods

A comparison of two approaches to model-based knowledge acquisition

Acquisition of gradual knowledge

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