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GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
14 years 2 months ago
Approximating geometric crossover in semantic space
We propose a crossover operator that works with genetic programming trees and is approximately geometric crossover in the semantic space. By defining semantic as program’s eval...
Krzysztof Krawiec, Pawel Lichocki
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 4 months ago
Evolutionary Approach to Test Generation for Functional BIST
In the paper, an evolutionary approach to test generation for functional BIST is considered. The aim of the proposed scheme is to minimize the test data volume by allowing the dev...
Y. A. Skobtsov, D. E. Ivanov, V. Y. Skobtsov, Raim...
CEC
2010
IEEE
13 years 7 months ago
Genetic programming for Expert Systems
— Genetic programming is the usage of the paradigm of survival of the fittest in scientific computing. It is applied to evolve solutions to problems where dependencies between ...
Konrad Sickel, Joachim Hornegger
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 1 months ago
Dormant program nodes and the efficiency of genetic programming
In genetic programming, there is a tendency for individuals in a population to accumulate fragments of code – often called introns – which are redundant in the fitness evaluat...
David Jackson
ITSSA
2006
116views more  ITSSA 2006»
13 years 7 months ago
A Genetic Programming Approach to Automated Test Generation for Object-Oriented Software
: This article proposes a new method for creating test software for object-oriented systems using a genetic programming approach. It is believed that this approach is advantageous ...
Arjan Seesing, Hans-Gerhard Groß