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» On the Brittleness of Evolutionary Algorithms
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FLAIRS
2008
15 years 8 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...
DAS
2008
Springer
15 years 8 months ago
Exploring Evolutionary Technical Trends from Academic Research Papers
Automatic Term Recognition (ATR) is concerned with discovering terminology in large volumes of text corpora. Technical terms are vital elements for understanding the techniques us...
Teng-Kai Fan, Chia-Hui Chang
DEXA
2008
Springer
123views Database» more  DEXA 2008»
15 years 8 months ago
Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
IWEC
2004
15 years 8 months ago
TEAM: The Team-Oriented Evolutionary Adaptability Mechanism
Many commercial computer games allow a team of players to match their skills against another team, controlled by humans or by the computer. Most players prefer human opponents, sin...
Sander Bakkes, Pieter Spronck, Eric O. Postma
ICAI
2003
15 years 8 months ago
Exploiting the Marginal Profits of Constraints with Evolutionary Multi-Objective Optimization Techniques
Many real-world search and optimization problems naturally involve constraint handling. Recently, quite a few heuristic methods were proposed to solve the nonlinear constrained op...
Zhenyu Yan, Wei Zhi, Lishan Kang