Neutrality of some boolean parity fitness landscapes is investigated in this paper. Compared with some well known contributions on the same issue, we define some new measures that help characterizing neutral landscapes, we use a new sampling methodology, which captures some features that are disregarded by uniform random sampling, and we introduce new genetic operators to define the neighborhood of tree structures. We compare the fitness landscape induced by two different sets of functional operators ({nand} and {xor ; not}). The different characteristics of the neutral networks seem to justify the different difficulties of these landscapes for genetic programming
Vanneschi, L., Pirola, Y., Collard, P., Tomassini, M., Verel, S., Mauri, G. (2006). A quantitative study of neutrality in GP boolean landscapes. In Proceedings of the 8th annual conference on Genetic and evolutionary computation, GECCO 2006 (pp.895-902). New York : ACM Press [10.1145/1143997.1144152].
A quantitative study of neutrality in GP boolean landscapes
VANNESCHI, LEONARDO;PIROLA, YURI;MAURI, GIANCARLO
2006
Abstract
Neutrality of some boolean parity fitness landscapes is investigated in this paper. Compared with some well known contributions on the same issue, we define some new measures that help characterizing neutral landscapes, we use a new sampling methodology, which captures some features that are disregarded by uniform random sampling, and we introduce new genetic operators to define the neighborhood of tree structures. We compare the fitness landscape induced by two different sets of functional operators ({nand} and {xor ; not}). The different characteristics of the neutral networks seem to justify the different difficulties of these landscapes for genetic programming
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