Automatically assigned DDC number: 00633

Manually assigned DDC number: 00633

Title: A Computational Model of Knowledge-Intensive Learning and Problem Solving


Subject: Agnar Aamodt A Computational Model of Knowledge-Intensive Learning and Problem Solving

Description: . If knowledge-based systems are to become more competent and robust in solving real world problems, they need to be able to adapt to an evolving domain and a changing environment. This paper proposes a computational model - a framework -for knowledge-intensive problem solving and learning from experience. The model has been instantiated in an architecture for knowledge-intensive case-based reasoning and learning called CREEK (Case-based Reasoning through Extensive Expert Knowledge). The importance of a thorough, extensive knowledge model to support the reasoning and learning processes is emphasized. In case-based reasoning a problem is solved by retrieving a similar past problem case, and using this case in solving the new problem. Learning becomes a process of extracting relevant information from a problem just solved, and integrating the new case into the existing case-base. The computational model presented combines case-based learning and reasoning with model-based and rule-based ...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1995-08-17

Pubyear: 0

Format: ps



Language: en

Rights: unrestricted


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