Case-base maintenance with multi-objective evolutionary algorithms

Abstract

CopyrightItems in 'OpenAIR@RGU', Robert Gordon University Open Access Institutional Repository, are protected by copyright and intellectual property law. If you believe that any material held in 'OpenAIR@RGU' infringes copyright, please contact openair-help@rgu.ac.uk with details. The item will be removed from the repository while the claim is investigated.The final publication is available at Springer via http://dx.doi.org/10.1007/s10844-015-0378-z Case-Base Maintenance with Multi-Objective Evolutionary AlgorithmsAbstract Case-Base Reasoning is a problem-solving methodology that uses old solved problems, called cases, to solve new problems. The case-base is the knowledge source where the cases are stored, and the amount of stored cases is critical to the problem-solving ability of the Case-Base Reasoning system. However, when the case-base has many cases, then performance problems arise due to the time needed to find those similar cases to the input problem. At this point, Case-Base Maintenance algorithms can be used to reduce the number of cases and maintain the accuracy of the Case-Base Reasoning system at the same time. Whereas Case-Base Maintenance algorithms typically use a particular heuristic to remove (or select) cases from the case-base, the resulting maintained case-base relies on the proportion of redundant and noisy cases that are present in the case-base, among other factors. That is, a particular Case-Base Maintenance algorithm is suitable for certain types of case-bases that share some indicators, such as redundancy and noise levels.In the present work, we consider Case-Base Maintenance as a multi-objective optimization problem, which is solved with a Multi-Objective Evolutionary Algorithm. To this end, a fitness function is introduced to measure three different objectives based on the Complexity Profile model. Our hypothesis is that the Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance may be used in a wider set of case-bases, achieving a good balance between the reduction of cases and the problem-solving ability of the CaseBased Reasoning system. Finally, from a set of the experiments, our proposed Multi-Objective Evolutionary Algorithm performing Case-Base Maintenance shows regularly good results with different sets of case-bases with different proportion of redundant and noisy cases.Eduardo Lupiani · Jose M. Juarez · Jose Palma University of Murcia, Spain E-mail: {elupiani,jmjuarez,jtpalma}@um.es Susan Craw · Stewart Massie Robert Gordon University, Scotland, UK E-mail: {s.craw,s.massie}@rgu.ac.uk 2 E. Lupiani et al.

Case Based Reasoning as a Model for Cognitive Artificial Intelligence

“…Cognition and meta-cognition for memory relates to case base maintenance and TCBR indexing. Memory based reflection has been useful to identify redundant or noisy cases for case base maintenance [17,35,36]. Memory based introspection has been used in facet learning and case indexing.…”

Self‐optimization for smelting process of fused magnesium furnace based on operation status assessment

“…A typical case reasoning process includes case representation, case retrieval, case reuse, case revision, case storage, and case maintenance. [43] Supposing x represents the case description part and f represents the solution description part, then, according to the description of the new problem, the same or most similar case in the case base can be found. The results of case retrieval directly affect the effect of solving new problems.…”

“…A typical case reasoning process includes case representation, case retrieval, case reuse, case revision, case storage, and case maintenance. [ 43 ]…”

A Review of Multi-objective Evolutionary Algorithms for Information Retrieval System

“…Lupiani et al, [1] have moved toward the Case-Base Maintenance task as a multi-target advancement issue that might be explained with a Multi-Objective Evolutionary Algorithm. Specifically, the issue of advancement is divided into three extraordinary and concurrent objectives, including limiting the separation of the present number of cases for the The accuracy needs to be improved along with approaches of big data.…”