Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
394931 | Information Sciences | 2011 | 15 Pages |
Abstract
The issue of controlling values of various parameters of an evolutionary algorithm is one of the most important and interesting areas of research in evolutionary computation. In this paper we propose two new parameter control strategies for evolutionary algorithms based on the ideas of reinforcement learning. These strategies provide efficient and low-cost adaptive techniques for parameter control and they preserve the original design of the evolutionary algorithm, as they can be included without changing either the structure of the algorithm nor its operators design.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Elizabeth Montero, MarĂa-Cristina Riff,