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TEC
2002
128views more  TEC 2002»
15 years 4 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
131
Voted
GECCO
2005
Springer
117views Optimization» more  GECCO 2005»
15 years 10 months ago
A study of evolutionary robustness in stochastically tiled polyominos
Given an evolutionary optimization problem with many possible genotypes for each phenotype this study investigates if the evolved genes for a given phenotype are more robust to po...
Justin Schonfeld, Daniel A. Ashlock
127
Voted
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 9 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 9 months ago
TestFul: using a hybrid evolutionary algorithm for testing stateful systems
This paper introduces TestFul, a framework for testing stateful systems and focuses on object-oriented software. TestFul employs a hybrid multi-objective evolutionary algorithm, t...
Matteo Miraz, Pier Luca Lanzi, Luciano Baresi
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 8 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace