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.

• Type: Conference
• Year: 2003
• Where: ISCIS
• Authors: Hamid Beigy, Mohammad Reza Meybodi
• Keywords: Action-set Learning Automaton, Continuous Action-set Learning, ISCIS 2003, Stochastic Optimization Problems