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» Solving iterated functions using genetic programming
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113
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MFCS
2004
Springer
15 years 8 months ago
Approximating Boolean Functions by OBDDs
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
Andre Gronemeier
CNSR
2006
IEEE
139views Communications» more  CNSR 2006»
15 years 9 months ago
Genetic Programming Based WiFi Data Link Layer Attack Detection
This paper presents a genetic programming based detection system for Data Link layer attacks on a WiFi network. We explore the use of two different fitness functions in order to ...
Patrick LaRoche, A. Nur Zincir-Heywood
130
Voted
ADBIS
2005
Springer
100views Database» more  ADBIS 2005»
15 years 9 months ago
Evolutionary Learning of Boolean Queries by Genetic Programming
Abstract. The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its...
Suhail S. J. Owais, Pavel Krömer, Václ...
ICANNGA
2009
Springer
203views Algorithms» more  ICANNGA 2009»
15 years 10 months ago
NEAT in HyperNEAT Substituted with Genetic Programming
In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
Zdenek Buk, Jan Koutník, Miroslav Snorek
119
Voted
GECCO
2007
Springer
200views Optimization» more  GECCO 2007»
15 years 9 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