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» Adapting binary fitness functions in Genetic Algorithms
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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...
ENGL
2007
103views more  ENGL 2007»
14 years 9 months ago
Fault Diagnosis of Manufacturing Processes via Genetic Algorithm Approach
—Instantaneous detection and diagnosis of various faults and break-downs in industrial processes is required to reduce production losses and damage to equipments. A solved knowle...
Stefania Gallova
ICML
2009
IEEE
15 years 10 months ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis
CIMCA
2005
IEEE
15 years 3 months ago
A New Evolutionary Algorithm for Determining the Optimal Number of Clusters
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Wei Lu, Issa Traoré
GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
15 years 3 months ago
Learning building block structure from crossover failure
In the classical binary genetic algorithm, although crossover within a building block (BB) does not always cause a decrease in fitness, any decrease in fitness results from the ...
Zhenhua Li, Erik D. Goodman