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» Automated Learning of Rules Using Genetic Operators
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GPEM
2000
121views more  GPEM 2000»
13 years 7 months ago
Bayesian Methods for Efficient Genetic Programming
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Byoung-Tak Zhang
SEAL
1998
Springer
13 years 12 months ago
Automating Space Allocation in Higher Education
The allocation of office space in any large institution is usually a problematical issue, which often demands a substantial amount of time to perform manually. The result of this a...
Edmund K. Burke, D. B. Varley
ICCBR
2003
Springer
14 years 27 days ago
Using Evolution Programs to Learn Local Similarity Measures
Abstract. The definition of similarity measures is one of the most crucial aspects when developing case-based applications. In particular, when employing similarity measures that ...
Armin Stahl, Thomas Gabel
GECCO
2008
Springer
201views Optimization» more  GECCO 2008»
13 years 8 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
14 years 1 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong