The neutrality of genetic programming Boolean function landscapes is investigated in this paper. Compared with some well-known contributions on the same issue, (i) we first define new measures which help in characterizing neutral landscapes; (ii) we use a new sampling methodology, which captures features that are disregarded by uniform random sampling; (iii) we introduce new genetic operators to define the neighborhood of tree structures; and (iv) we compare the fitness landscape induced by different sets of functional operators. This study indicates the existence of a relationship between our neutrality measures and the performance of genetic programming for the problems studied.
Vanneschi, L., Pirola, Y., Mauri, G., Tomassini, M., Collard, P., Verel, S. (2012). A study of the neutrality of Boolean function landscapes in genetic programming. THEORETICAL COMPUTER SCIENCE, 425(30 March 2012), 34-57 [10.1016/j.tcs.2011.03.011].
A study of the neutrality of Boolean function landscapes in genetic programming
VANNESCHI, LEONARDO
;PIROLA, YURI;MAURI, GIANCARLO;
2012
Abstract
The neutrality of genetic programming Boolean function landscapes is investigated in this paper. Compared with some well-known contributions on the same issue, (i) we first define new measures which help in characterizing neutral landscapes; (ii) we use a new sampling methodology, which captures features that are disregarded by uniform random sampling; (iii) we introduce new genetic operators to define the neighborhood of tree structures; and (iv) we compare the fitness landscape induced by different sets of functional operators. This study indicates the existence of a relationship between our neutrality measures and the performance of genetic programming for the problems studied.
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