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GECCO
2000
Springer
122views Optimization» more  GECCO 2000»
14 years 2 months ago
Genetic Programming with Statically Scoped Local Variables
This paper presents an extension to genetic programming to allow the evolution of programs containing local variables with static scope which obey the invariant that all variables...
Evan Kirshenbaum
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
14 years 5 months ago
Adaptive genetic programming for option pricing
Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex prob...
Zheng Yin, Anthony Brabazon, Conall O'Sullivan
GECCO
2009
Springer
128views Optimization» more  GECCO 2009»
14 years 3 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
2010
Springer
218views Optimization» more  GECCO 2010»
14 years 2 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
2006
Springer
139views Optimization» more  GECCO 2006»
14 years 2 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule