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ISCIS
2003
Springer

A New Continuous Action-Set Learning Automaton for Function Optimization

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A New Continuous Action-Set Learning Automaton for Function Optimization
In this paper, we study an adaptive random search method based on continuous action-set learning automaton for solving stochastic optimization problems in which only the noisecorrupted value of function at any chosen point in the parameter space is available. We first introduce a new continuous action-set learning automaton (CALA) and study its convergence properties. Then we give an algorithm for optimizing an unknown function. r 2005 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Hamid Beigy, Mohammad Reza Meybodi
Added 07 Jul 2010
Updated 07 Jul 2010
Type Conference
Year 2003
Where ISCIS
Authors Hamid Beigy, Mohammad Reza Meybodi
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