Automatically assigned DDC number: 006333

Manually assigned DDC number: 006333

Number of references: 8

Title: Towards Improving Case Adaptability with a Genetic Algorithm

Author:

Author:

Subject: Lisa Purvis,Salil Athalye Towards Improving Case Adaptability with a Genetic Algorithm

Description: . Case combination is a difficult problem in Case Based Reasoning, as sub-cases often exhibit conflicts when merged together. In our previous work we formalized case combination by representing each case as a constraint satisfaction problem, and used the minimum conflicts algorithm to systematically synthesize the global solution. However, we also found instances of the problem in which the minimum conflicts algorithm does not perform case combination efficiently. In this paper we describe those situations in which initially retrieved cases are not easily adaptable, and propose a method by which to improve case adaptability with a genetic algorithm. We introduce a fitness function that maintains as much retrieved case information as possible, while also perturbing a sub-solution to allow subsequent case combination to proceed more efficiently. 1 Introduction One of the more difficult problems in Case Based Reasoning (CBR) is how to adapt a case to fit the new situation requirements [2...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1998-04-15

Pubyear: 1997

Format: ps

Identifier: http://citeseer.ist.psu.edu/173187.html

Source: http://www-rfcc.cse.uconn.edu/www/LisaPurvis/iccbr97-final.ps

Language: en

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Rights: unrestricted

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