Semantics based crossover for boolean problems
Nguyen Quang Uy, Nguyễn Xuân Hoài, Michael O’Neill, Bob McKay · 2010
This paper investigates the role of semantic diversity and locality of crossover operators in. Genetic Programming (GP) for Boolean problems. We propose methods for measuring and storing semantics of subtrees in Boolean domains using Trace Semantics, and design several new crossovers on this basis. They can be categorised into two classes depending on their purposes: promoting semantic diversity or improving semantic locality. We test the operators on several well-known Boolean problems, comparing them with Standard GP Crossovers and with the Semantic Driven Crossover of Beadle and Johnson. The experimental results show the positive effects both of promoting semantic diversity, and of improving semantic locality, in crossover operators. They also show that the latter has a greater positive effect on GP performance than the former.