On Estimation Distribution Algorithms

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“On Estimation Distribution Algorithms” by R. Santana and A. Ochoa. In Proceedings of the Genetic and Evolutionary Computation Conference GECCO-1999, Workshop Program, (Wu A. S., ed.), (Orlando, FL), 1999.

Abstract

The main goal of the dissertation research is the design of efficient Estimation Distribution Algorithms based on non simply connected probabilistic networks. This work is part of a more ambitious ongoing research on Low Cost Evolutionary Algorithms (LCEA). Other important areas to be covered with the dissertation are: 1) The integration of different theories about GA in order to explain successful results of EDA in the context of evolutionary computation. 2) Define ways of incorporating knowledge about the problem domain, prior to the beginning and during the function optimization . 3) To study the recognized sources of hardness for GAâÂÂs in the framework of EDA. 4) Define measures to evaluate the quality of the different search strategies used. We now describe some aspect of the current research in these topics.

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BibTeX entry:

@inproceedings{Santana_and_Ochoa:1999a,
   author = {R. Santana and A. Ochoa},
   editor = {Wu A. S.},
   title = {On {E}stimation {D}istribution {A}lgorithms},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation
	Conference {GECCO}-1999, Workshop Program},
   pages = {402},
   publisher = {Morgan Kaufmann Publishers, San Francisco, CA},
   address = {Orlando, FL},
   year = {1999}
}

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