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IICAI
2003
13 years 11 months ago
Performance Analysis of an Acyclic Genetic approach to Learn Bayesian Network Structure
Abstract. We introduce a new genetic algorithm approach for learning a Bayesian network structure from data. Our method is capable of learning over all node orderings and structure...
Pankaj B. Gupta, Vicki H. Allan
SOFTCO
2004
Springer
14 years 3 months ago
Designing Neural Networks Using Gene Expression Programming
Abstract. An artificial neural network with all its elements is a rather complex structure, not easily constructed and/or trained to perform a particular task. Consequently, severa...
Cândida Ferreira
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
14 years 3 months ago
Studying the Advantages of a Messy Evolutionary Algorithm for Natural Language Tagging
The process of labeling each word in a sentence with one of its lexical categories (noun, verb, etc) is called tagging and is a key step in parsing and many other language processi...
Lourdes Araujo
EUSFLAT
2003
165views Fuzzy Logic» more  EUSFLAT 2003»
13 years 11 months ago
Genetic fuzzy systems to evolve coordination strategies in competitive distributed systems
This paper suggests an evolutionary approach to design coordination strategies, a key issue in distributed intelligent systems. We focus on competitive strategies in the form of f...
Igor Walter, Fernando A. C. Gomide
GECCO
2005
Springer
232views Optimization» more  GECCO 2005»
14 years 3 months ago
A hardware pipeline for function optimization using genetic algorithms
Genetic Algorithms (GAs) are very commonly used as function optimizers, basically due to their search capability. A number of different serial and parallel versions of GA exist. ...
Malay Kumar Pakhira, Rajat K. De