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» Evolutionary Computation for Modeling and Optimization
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ERSHOV
2003
Springer
15 years 11 months ago
Complexity of Model Checking by Iterative Improvement: The Pseudo-Boolean Framework
We present several new algorithms as well as new lower and upper bounds for optimizing functions underlying infinite games pertinent to computer-aided verification.
Henrik Björklund, Sven Sandberg, Sergei G. Vo...
GECCO
2009
Springer
191views Optimization» more  GECCO 2009»
16 years 1 months ago
Evolvable malware
The concept of artificial evolution has been applied to numerous real world applications in different domains. In this paper, we use this concept in the domain of virology to ev...
Sadia Noreen, Shafaq Murtaza, M. Zubair Shafiq, Mu...
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
16 years 1 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2010
Springer
150views Optimization» more  GECCO 2010»
15 years 11 months ago
Object-level recombination of commodity applications
This paper presents ObjRecombGA, a genetic algorithm framework for recombining related programs at the object file level. A genetic algorithm guides the selection of object file...
Blair Foster, Anil Somayaji
GECCO
2010
Springer
129views Optimization» more  GECCO 2010»
15 years 11 months 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