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CEC
2009
IEEE
10 years 9 months ago
Mixed Mutation Strategy Embedded Differential Evolution
Differential evolution (DE) is a powerful yet simple evolutionary algorithm for optimizing real valued optimization problems. Traditional investigations with differential evolution...
Millie Pant, Musrrat Ali, Ajith Abraham
CEC
2009
IEEE
10 years 9 months ago
Semantically driven mutation in genetic programming
—Using semantic analysis, we present a technique known as semantically driven mutation which can explicitly detect and apply behavioural changes caused by the syntactic changes i...
Lawrence Beadle, Colin G. Johnson
CEC
2009
IEEE
10 years 9 months ago
Evolving modular neural-networks through exaptation
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...
Jean-Baptiste Mouret, Stéphane Doncieux
CEC
2009
IEEE
10 years 9 months ago
Intensity isotherms and distributions on oligonucleotide microarrays
We describe a physico-chemical model relating measured fluorescence intensities on oligonucleotide microarrays to the underlying specific target concentration in the hybridized so...
Conrad J. Burden
CEC
2009
IEEE
10 years 9 months ago
Constructing test problems for bilevel evolutionary multi-objective optimization
— Many real-world problems demand a feasible solution to satisfy physical equilibrium, stability, or certain properties which require an additional lower level optimization probl...
Kalyanmoy Deb, Ankur Sinha
CEC
2009
IEEE
10 years 9 months ago
Multi-start JADE with knowledge transfer for numerical optimization
— JADE is a recent variant of Differential Evolution (DE) for numerical optimization, which has been reported to obtain some promising results in experimental study. However, we ...
Fei Peng, Ke Tang, Guoliang Chen, Xin Yao
CEC
2009
IEEE
10 years 9 months ago
Hyper-learning for population-based incremental learning in dynamic environments
— The population-based incremental learning (PBIL) algorithm is a combination of evolutionary optimization and competitive learning. Recently, the PBIL algorithm has been applied...
Shengxiang Yang, Hendrik Richter
CEC
2009
IEEE
10 years 9 months ago
On-line neuroevolution applied to The Open Racing Car Simulator
— The application of on-line learning techniques to modern computer games is a promising research direction. In fact, they can be used to improve the game experience and to achie...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
CEC
2009
IEEE
10 years 9 months ago
An adaptive coevolutionary Differential Evolution algorithm for large-scale optimization
— In this paper, we propose a new algorithm, named JACC-G, for large scale optimization problems. The motivation is to improve our previous work on grouping and adaptive weightin...
Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao, Art...
CEC
2009
IEEE
10 years 9 months ago
Biocybernetic loop: From awareness to evolution
—Developing systems that support people in everyday life in a discrete and effective way is an ultimate goal of a new generation of technical systems. Physiological computing rep...
Nikola B. Serbedzija, Stephen H. Fairclough
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