Titlebook: Case-Based Reasoning; A Concise Introducti Beatriz López Book 2013 Springer Nature Switzerland AG 2013

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Operations Research in the Airline Industry, no learning effort is dedicated when storing cases in memory, but is at problem-solving time, practical CBR requires the use of more eager methods to improve efficiency in problem solving. Learning can be applied to obtain case models, as prototypes, to recognize the relevant features of the domai

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A Practical Macroeconometric Modelsystems. The behavior of a system should be predictable, thus the formal specification and then verification of CBR systems should be possible. CBR, as a methodology, encompasses several stages, while formal approaches used to cover part of them. For example, description logic focuses on knowledge r

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Observers and Macroeconomic Systemsilar problems. Past experiences or cases are stored by keeping all the particular information of a problem-solving past episode, without dropping any particularities out, the removal of which could lead to the generation of general patterns. The experiences are, by themselves, part of the domain mod

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Christian Hurson,Nadine Ricci-XellaCase-based reasoning (CBR) is a methodology for developing knowledge-based systems where the central issue is past cases or experiences. Case-based reasoning means solving problems based on past experiences, remembering previous cases to guide the solution to current problems, and adapting past solutions to new problems.

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Reasoning and Decision Making,ng episodes) stored in the knowledge base. It involves the retrieve and reuse stages of CBR, as shown in Figure 3.1. Moreover, as it is possible to observe in the diagram, some feedback can be obtained in the revise stage and a remade solution can be generated and annotated with the evaluation outcome.

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