J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer, Model-based and incremental knowledge engineering: the MIKE approach , in: J. Cuena, eds., Knowledge Oriented Software Design (Elsevier, Amsterdam, 1993) 139--168.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....or data driven. Procedural control defines the sequencing and possible iteration of subtasks. Such control can be modeled as finite state automata where the states of the automata correspond to subtasks and the transitions represent control flow. Alternatively, dynamic logic has been used [3] . However, such formalism failed to capture opportunistic activations of subtasks when data are become available asynchronously. Thus, PROTG II does not have a strong formalism for defining control flow yet. To guide implementation and to inform potential users of the method, we specify ....

J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer, Model-based and incremental knowledge engineering: the MIKE approach , in: J. Cuena, eds., Knowledge Oriented Software Design (Elsevier, Amsterdam, 1993) 139--168.

....this gap between a conceptual model its implementation, and, to bridge it, they view KBS development as an incremental (though, nonlinear) process, in which subsequently more detailed models are constructed. Several knowledge engineering approaches such as Kads [Schreiber et al. 1993] Mike [Angele et al. 1993] and Task [Pierret Golbreich, 1994] advocate the use of the following increasingly more detailed models: conceptual model (informal, but structured) formal model (language with a mathematically defined syntax and semantics) design model (specifies the system architecture, and the data ....

Angele, J., Fensel, D., Landes, D., Neubert, S., & Studer, R. (1993). Model-based and incremental knowledge engineering: the MIKE approach. In Cuena, J., editor, Knowledge Oriented Software Design, IFIP Transactions A-27, Amsterdam. Elsevier.

....domain knowledge via inference structures to a set of rules. The external acquisition cycle operationalizes the produced rule set and translates knowledge into objects, relations, methods and an inference engine. An approach to incremental knowledge acquisition and modeling is used in MIKE [Angele 93, Neubert 93] MIKE is furthermore characterized by modelbased knowledge engineering, by several levels for expertise representation and by the possibility to reuse existing models. MIKE covers all the development steps fromknowledge elicitation, interpretation and formalization up to ....

J. Angele, D. Fensel, S. Neubert and R. Studer. Model-based and incremental knowledge engineering : The MIKE approach. In Proc. of the IFIP TC12 Workshop on Artificial Intelligence from the Information Processing Perspective - AIFIPP'92. Elsevier, 1993.

....language KARL, c.f. Angele, Fensel and Studer (1994) and Fensel (1995a) was combined with an implementation by a configurable role limiting method CRLM, c.f. Poeck and Gappa (1993) and Poeck (1995) KARL was developed in the MIKE project Model based and Incremental Knowledge Engineering, cf. Angele, Fensel, Landes, Neubert and Studer (1993), and allows a formal and operational specification of knowledge based systems. CRLM Configurable RoleLimiting Method Approach emerged from experiences with other role limiting method shells (RLM) like D3 CLASSIKA, c.f. Puppe and Gappa (1992) and COKE, c.f. Poeck and Puppe (1992) over the last ....

Angele, J., Fensel, D., Landes, D., Neubert, S. & Studer, R. ( 1993). Model-Based and Incremental Knowledge Engineering: The MIKE Approach. Knowledge Oriented Software Design, J. Cuena (ed.), IFIP Transactions A-27, Elsevier, Amsterdam, 139-168.

....quality criteria. The approach is based on identifying and supporting adequate transition paths and activities on models in order to achieve particular quality criteria. 1. Introduction and motivation Modern knowledge engineering (KE) methodologies such as CommonKADS [20] VITAL [10] MIKE [3], TASK [16] are successful in providing structure to the development process of knowledge based systems (KBSs) by identifying intermediate models and defining the languages and organisation of these models. These methodologies have been originally set up in response to the industrial need for a ....

....transformations are possible. This facilitates not only validation and verification of the models, but also their modifications. The nature and structure of the different models have been brought to light in past research in Knowledge Engineering (e.g. CommonKADS [20] VITAL [21] MIKE [3], TASK [16] and include the following: A conceptual model (CM) is dedicated to capture the expertise in an informal, but structured way. A CM describes the different types and roles of knowledge in reasoning tasks. It facilitates initial KBS specification and human s understanding of the KBS ....

J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer. Model-based and incremental knowledge engineering: the MIKE approach. In J. Cuena, editor, Knowledge Oriented Software Design, IFIP Transactions A-27, Amsterdam, 1993. Elsevier.

....knowledge modeling, interoperability standards and ontologies. PSMs are made accessible by describing them in the product description language UPML (Unified Problem solving Method description Language) whose development is based on a unification of current knowledge modeling approaches [25, 9, 28, 1, 23, 27]. For letting heterogeneous PSMs work together, we use CORBA [22, 15] Ontologies are used to describe the different worlds of the agents involved, which have to be mapped onto each other. In a nutshell, the two tasks we aim to solve, are the following (illustrated in Figure 1) A broker program ....

J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer. Model-based and incremental knowledge engineering: the MIKE approach. In J. Cuena, editor, Knowledge Oriented Software Design, IFIP Transactions A-27, Amsterdam, 1993. Elsevier.

....MODEL K [46] OMOS [51] MoMo [81, 31] all from GMD in Bonn) FORKADS [82, 83] from IBM Heidelberg, ML) 2 [76] from Amsterdam. Other languages were not directly based on KADS, but were based on a conceptual model closely related to KADS: KARL [4, 25] from Karlsruhe based on the MIKE model [3], K BS SF [41] from the Dutch Telecom based on the VITAL model [45] and TFL [63] from Paris based on the TASK model. Yet other languages were not originally based on KADS, but it was shown how they could be used for KADSlike models: QIL [64] from Nottingham, GCLA [5] from SICS in Sweden, AIDE ....

....requirements. The same argument about the close correspondence between informal and formal models can also be used to rule out the following: Myth 7: Formal methods are unacceptable to users In particular the graphical representations available for many formal languages in KE (see e.g. MIKE [3]) and the possibility to interpret the formal constructions in terms of the underlying conceptual model form a significant bridge to users and domain experts alike. Myth 8: Formal methods are only useful in safety critical systems It is true that safety critical applications can gain obvious ....

J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer. Model-based and incremental knowledge engineering: The MIKE approach. In J. Cuena, editor, Knowledge Oriented Software Design, number A-27 in IFIP Transactions, Amsterdam, 1993. North Holland.

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J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer. Model based and Incremental Knowledge Engineering: The MIKE Approach. In J. Cuena, editor, Knowledge Oriented Software Design, volume A-27, pages 139 -- 168, Amsterdam, 1993. IFIP Transactions, North Holland.

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Angele, J., Fensel, D., Landes, D., Neubert, S., and Studer, R. (1993). Model-Based and Incremental Knowledge Engineering: The MIKE Approach. In Knowledge Oriented Software Design, J. Cuena (Ed.). IFIP Transactions A-27, Elsevier, Amsterdam, 139-168.

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Angele J., Fensel D., Landes D., Neubert S., Studer R. (1992): "Model-Based and Incremental Knowledge Engineering: The MIKE Approach". Proc. Artificial Intelligence from the Information Processing (Workshop AIFIPP'92), Madrid, 1992.

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