A New Continuous Action-Set Learning Automaton for Function Optimization

نویسندگان

  • Hamid Beigy
  • Mohammad Reza Meybodi
چکیده

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.

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تاریخ انتشار 2003