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EVOW
2010
Springer
13 years 11 months ago
On the Benefit of Sub-optimality within the Divide-and-Evolve Scheme
Divide-and-Evolve (DaE) is an original "memeticization" of Evolutionary Computation and Artificial Intelligence Planning. DaE optimizes either the number of actions, or t...
Jacques Bibai, Pierre Savéant, Marc Schoena...
ATAL
2009
Springer
14 years 2 months ago
Evolutionary testing of autonomous software agents
A system built in terms of autonomous agents may require even greater correctness assurance than one which is merely reacting to the immediate control of its users. Agents make su...
Cu D. Nguyen, Anna Perini, Paolo Tonella, Simon Mi...
GECCO
2009
Springer
161views Optimization» more  GECCO 2009»
14 years 2 months ago
Are evolutionary rule learning algorithms appropriate for malware detection?
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...
CEC
2007
IEEE
14 years 2 months ago
Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
Dimo Brockhoff, Eckart Zitzler
EPIA
2007
Springer
14 years 2 months ago
Improving Evolutionary Algorithms with Scouting
The goal of an Evolutionary Algorithm(EA) is to find the optimal solution to a given problem by evolving a set of initial potential solutions. When the problem is multi-modal, an ...
Konstantinos Bousmalis, Gillian M. Hayes, Jeffrey ...