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» Genetic programming and evolutionary generalization
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ACSAC
2007
IEEE
15 years 4 months ago
Automated Vulnerability Analysis: Leveraging Control Flow for Evolutionary Input Crafting
We present an extension of traditional "black box" fuzz testing using a genetic algorithm based upon a Dynamic Markov Model fitness heuristic. This heuristic allows us t...
Sherri Sparks, Shawn Embleton, Ryan Cunningham, Cl...
GECCO
2007
Springer
293views Optimization» more  GECCO 2007»
15 years 3 months ago
Solving the artificial ant on the Santa Fe trail problem in 20, 696 fitness evaluations
In this paper, we provide an algorithm that systematically considers all small trees in the search space of genetic programming. These small trees are used to generate useful subr...
Steffen Christensen, Franz Oppacher
86
Voted
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
15 years 3 months ago
Goal-oriented preservation of essential genetic information by offspring selection
This contribution proposes an enhanced and generic selection model for Genetic Algorithms (GAs) and Genetic Programming (GP) which is able to preserve the alleles which are part o...
Michael Affenzeller, Stefan Wagner 0002, Stephan M...
SEAL
1998
Springer
15 years 1 months ago
Genetic Programming with Active Data Selection
Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
Byoung-Tak Zhang, Dong-Yeon Cho
76
Voted
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 3 months ago
Diversity as a selection pressure in dynamic environments
Evolutionary algorithms (EAs) are widely used to deal with optimization problems in dynamic environments (DE) [3]. When using EAs to solve DE problems, we are usually interested i...
Lam Thu Bui, Jürgen Branke, Hussein A. Abbass