PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bringing Evolutionary Computation to Industrial Applications with GUIDE
Luis DaCosta and Marc Schoenauer
In: Genetic and Evolutionary Computation Conference 2009 (2009) ACM , pp. 1467-1474.

Abstract

Evolutionary Computation is an exciting research eld with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitable knowledge about the solution space is very hard and/or expensive to obtain). However, Evolutionary Algorithms are rarely used outside the circle of knowledgeable practitioners, and in that way have not achieved a status of useful enough tool to assist \general" researchers. We think that part of the blame is the lack of practical implementations of research eorts re ecting a unifying common ground in the field. In this communication we present GUIDE, a software framework incorporating some of the latest results from the EC research community and oering a Graphical User Interface that allows the straightforward manipulation of evolutionary algorithms. From a high-level description provided by the user it generates the code that is needed to run an evolutionary algorithm in a specied existing library (as of March 2009, EO and ECJ are the possible targeted libraries). GUIDE's GUI allows users to acquire a straightforward understanding of EC ideas, while at the same time providing them with a sophisticated research tool. In this communication we present 3 industrial case studies using GUIDE as one of the main tools in order to perform software testing on large, complex systems.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:6900
Deposited By:Marc Schoenauer
Deposited On:12 April 2010