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» A framework for the description of evolutionary algorithms
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BMVC
2002
13 years 10 months ago
A Qualitative, Multi-scale Grammar For Image Description and Analysis
A qualitative image description grammar with automatic image fitting and object modelling algorithms is presented. The grammar is based on assigning a square sub-region of an imag...
Derek R. Magee
GECCO
2004
Springer
119views Optimization» more  GECCO 2004»
14 years 1 months ago
Topological Interpretation of Crossover
Abstract. In this paper we give a representation-independent topological definition of crossover that links it tightly to the notion of fitness landscape. Building around this defi...
Alberto Moraglio, Riccardo Poli
AIIA
2007
Springer
14 years 1 months ago
Structured Hidden Markov Model: A General Framework for Modeling Complex Sequences
Structured Hidden Markov Model (S-HMM) is a variant of Hierarchical Hidden Markov Model that shows interesting capabilities of extracting knowledge from symbolic sequences. In fact...
Ugo Galassi, Attilio Giordana, Lorenza Saitta
CEC
2005
IEEE
14 years 1 months ago
Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies
Genetic algorithms (GAs) and evolution strategies (ESs) are two widely used evolutionary algorithms. The main differences between GAs and ESs lie in their representations and varia...
Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff
GECCO
2004
Springer
119views Optimization» more  GECCO 2004»
14 years 1 months ago
Learning Environment for Life Time Value Calculation of Customers in Insurance Domain
A critical success factor in Insurance business is its ability to use information sources and contained knowledge in the most effective way. Its profitability is obtained through t...
Andrea Tettamanzi, Luca Sammartino, Mikhail Simono...