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GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
15 years 10 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
ICNC
2005
Springer
15 years 10 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
GECCO
2005
Springer
15 years 10 months ago
Probing for limits to building block mixing with a tunably-difficult problem for genetic programming
This paper describes a tunably-difficult problem for genetic programming (GP) that probes for limits to building block mixing and assembly. The existence of such a problem can be ...
Jason M. Daida, Michael E. Samples, Matthew J. Byo...
GECCO
2004
Springer
15 years 10 months ago
Evolving Quantum Circuits and Programs Through Genetic Programming
Abstract. Spector et al. have shown [1],[2],[3] that genetic programming can be used to evolve quantum circuits. In this paper, we present new results in this field, introducing p...
Paul Massey, John A. Clark, Susan Stepney
GECCO
2003
Springer
114views Optimization» more  GECCO 2003»
15 years 10 months ago
A Linear Genetic Programming Approach to Intrusion Detection
Abstract. Page-based Linear Genetic Programming (GP) is proposed and implemented with two-layer Subset Selection to address a two-class intrusion detection classification problem a...
Dong Song, Malcolm I. Heywood, A. Nur Zincir-Heywo...