The essence of problem-solving methods: making assumptions to gain efficiency
International Journal of Human-Computer Studies
Modal change logic (MCL): specifying the reasoning of knowledge-based systems
Data & Knowledge Engineering
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
The Knowledge Acquisition and Representation Language, KARL
IEEE Transactions on Knowledge and Data Engineering
Toward a Competence Theory of Diagnosis
IEEE Expert: Intelligent Systems and Their Applications
CommonKADS: A Comprehensive Methodology for KBS Development
IEEE Expert: Intelligent Systems and Their Applications
Experiences with Modelling Issues in Building Probabilistic Networks
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Problem-solving methods: understanding, description, development, and reuse
Problem-solving methods: understanding, description, development, and reuse
The KAMET II methodology: Knowledge acquisition, knowledge modeling and knowledge generation
Expert Systems with Applications: An International Journal
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Different methodologies have been developed to solve various tasks such as classification, design, planning, scheduling and diagnosis. Diagnosis is a task of which the desired output is a malfunction of a system. KAMET (Knowledge-Acquisition Methodology) is a knowledge engineering methodology aimed to attack diagnosis tasks exclusively. In this article KAMET II, the second version of KAMET, will be presented with the objective of knowing its most important characteristics as well as its modeling notation which will subsequently be necessary for the knowledge bases, Problem-Solving Methods (PSMs) and the knowledge model specification. KAMET is a model-based methodology appointed to administer knowledge acquisition from multiple knowledge sources. The methodology provides a mechanism by means of which knowledge acquisition is achieved in an incremental fashion and in a cooperative environment. One important feature is the specification used to describe knowledge-based systems independently of their implementation. A four-component architecture is presented to achieve this goal and to allow component separation and consequently component reuse.