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Author manuscript, published in "FOGA- Foundations of Genetic Algorithms XII- 2013 (2013)" Noisy Optimization Complexity Under Locality Assumption

By Jérémie Decock and Tao TeamOlivier Teytaud and Tao Team

Abstract

In spite of various recent publications on the subject, there are still gaps between upper and lower bounds in evolutionary optimization for noisy objective function. In this paper we reduce the gap, and get tight bounds within logarithmic factors in the case of small noise and no long-distance influence on the objective function

Topics: Categories and Subject Descriptors G.1.6 [Mathematics of Computing, Numerical Analysis—Optimization General Terms Theory Keywords Noisy optimization
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.373.870
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