An Evolution Strategy Using a Continuous Version of the Gray-Code Neighbourhood Distribution

Jonathan E. Rowe and Dena Hidovi

Abstract. We derive a continuous probability distribution which generates neighbours of a point in an interval in a similar way to the bitwise mutation of a Gray code binary string. This distribution has some interesting scale-free properties which are analogues of properties of the Gray code neighbourhood structure. A simple (1+1)-ES using the new distribution is proposed and evaluated on a set of benchmark problems, on which it performs remarkably well. The critical parameter is the precision of the distribution, which corresponds to the string length in the discrete case. The algorithm is also tested on a difficult real-world problem from medical imaging, on which it also performs well. Some observations concerning the scale-free properties of the distribution are made, although further analysis is required to understand why this simple algorithm works so well.

LNCS 3102, p. 725 ff.

Full article in PDF

lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004