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EUROGP
2005
Springer

Operator-Based Distance for Genetic Programming: Subtree Crossover Distance

9 years 8 months ago
Operator-Based Distance for Genetic Programming: Subtree Crossover Distance
Abstract. This paper explores distance measures based on genetic operators for genetic programming using tree structures. The consistency between genetic operators and distance measures is a crucial point for analytical measures of problem difficulty, such as fitness distance correlation, and for measures of population diversity, such as entropy or variance. The contribution of this paper is the exploration of possible definitions and approximations of operator-based edit distance measures. In particular, we focus on the subtree crossover operator. An empirical study is presented to illustrate the features of an operator-based distance. This paper makes progress toward improved algorithmic analysis by using appropriate measures of distance and similarity.
Steven M. Gustafson, Leonardo Vanneschi
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where EUROGP
Authors Steven M. Gustafson, Leonardo Vanneschi
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