We introduce Prioritized Grammar Enumeration (PGE), a deterministic Symbolic Regression
(SR) algorithm using dynamic programming techniques. PGE maintains the tree-based …

The crossover operator has been considered ldquothe centre of the stormrdquo in genetic
programming (GP). However, many existing GP approaches to object recognition suggest …

This paper presents a genetic programming (GP) based approach for designing classifiers
with feature selection using a modified crossover operator. The proposed GP methodology …

An often-mentioned issue with Grammatical Evolution is that a small change in the
genotype, through mutation or crossover, may completely change the meaning of all of the …

This chapter gives a narrative of the problems we encountered using genetic programming
to build a symbolic regression tool for large-scale, time-constrained regression problems. It …

Beside the ease and speed brought by automated synthesis stations and reactors
technologies in materials science, adapted informatics tools must be further developed in …

This research builds on the hypothesis that the use of different fitness measures on the
different generations of genetic programming (GP) is more effective than the convention of …

Visual analytics is a human-machine collaboration to data modeling where extraction of the
most informative features plays an important role. Although feature extraction is a multi …

Crossover in Genetic Programming is mostly a destructive operator, generally producing
children worse than the parents and occasionally producing those who are better. A recently …

The genetic programming (GP) paradigm, which applies the Darwinian principle of evolution
to hierarchical computer programs, has been applied with breakthrough success in various …