Retrieval, reuse, revision and retention in

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Retrieval, reuse, revision, and retention in casebased

Abstract. There may be advantages to be gained by combining Case-Based Reasoning (CBR) techniques with numerical models. In this paper we consider how CBR can be used as a flexible query engine to improve the usability of numerical models. Particularly they can help to solve inverse and mixed problems, and to solve constraint problems. We discuss this idea with reference to the illustrative example of a pneumatic conveyor. We describe a model of the problem of particle degradation in such a conveyor, and the problems faced by design engineers. The solution of these problems requires a system that allows iterative sharing of control between user, CBR system, and numerical model. This multi-initiative interaction is illustrated for the pneumatic conveyor by means of Unified Modeling Language (UML) collaboration and sequence diagrams. We show approaches to the solution of these problems via a CBR tool. 1

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science

Case-base reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving: new problems are solved by reusing the solutions to similar problems that have been solved in the past. To date CBR has enjoyed considerable 2 R. LÓPEZ DE MÁNTARAS ET AL. success in a wide variety of problem solving tasks and domains. In this paper, following a brief overview of the traditional problem-solving cycle in case-based reasoning, we examine the cognitive science foundations of CBR and the relationship between CBR and analogical reasoning. We then go on to review a representative selection of CBR research on aspects of

Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision, and