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GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
14 years 13 days 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
IEAAIE
2004
Springer
14 years 1 months ago
Modeling Intrusion Detection Systems Using Linear Genetic Programming Approach
This paper investigates the suitability of linear genetic programming (LGP) technique to model efficient intrusion detection systems, while comparing its performance with artificia...
Srinivas Mukkamala, Andrew H. Sung, Ajith Abraham
ICSE
2009
IEEE-ACM
14 years 8 months ago
Automatically finding patches using genetic programming
Automatic repair of programs has been a longstanding goal in software engineering, yet debugging remains a largely manual process. We introduce a fully automated method for locati...
Westley Weimer, ThanhVu Nguyen, Claire Le Goues, S...
CEC
2009
IEEE
14 years 2 months ago
Self modifying Cartesian Genetic Programming: Parity
— Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It differs from CGP by including primitive functions which modify the program. Beginni...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
14 years 1 months ago
Towards identifying populations that increase the likelihood of success in genetic programming
This paper presents a comprehensive, multivariate account of how initial population material is used over the course of a genetic programming run as while various factors influenc...
Jason M. Daida