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GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
15 years 9 months ago
A probabilistic functional crossover operator for genetic programming
The original mechanism by which evolutionary algorithms were to solve problems was to allow for the gradual discovery of sub-solutions to sub-problems, and the automated combinati...
Josh C. Bongard
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
15 years 9 months ago
Evolving stochastic processes using feature tests and genetic programming
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Brian J. Ross, Janine H. Imada
GECCO
2009
Springer
109views Optimization» more  GECCO 2009»
15 years 9 months ago
A genetic algorithm for learning significant phrase patterns in radiology reports
Radiologists disagree with each other over the characteristics and features of what constitutes a normal mammogram and the terminology to use in the associated radiology report. R...
Robert M. Patton, Thomas E. Potok, Barbara G. Beck...
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GECCO
2010
Springer
218views Optimization» more  GECCO 2010»
15 years 8 months ago
Cartesian genetic programming
This paper presents a new form of Genetic Programming called Cartesian Genetic Programming in which a program is represented as an indexed graph. The graph is encoded in the form o...
Julian Francis Miller, Simon L. Harding
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
15 years 8 months ago
Learning recursive programs with cooperative coevolution of genetic code mapping and genotype
The Probabilistic Adaptive Mapping Developmental Genetic Programming (PAM DGP) algorithm that cooperatively coevolves a population of adaptive mappings and associated genotypes is...
Garnett Carl Wilson, Malcolm I. Heywood