Advances in Genetic Programming,
Ch 23, Abstract
This chapter appears in
_Advances in Genetic Programming_, edited by
Kim Kinnear, published by the
MIT Press
Automatically Defined Features--The Simultaneous Evolution of
2-Dimensional Feature Detectors and an Algorithm for Using Them
David Andre
Although automatically defined functions (ADFcts) with genetic
programming (GP) appear to have great utility in a wide variety of
domains, their application to the automatic discovery of
2-dimensional features has been only moderately successful (Koza,
1993). Boolean functions of pixel inputs, although very general, may
not be the best representation for 2-dimensional features. This paper
describes a method for the simultaneous evolution of 2-dimensional
hit-miss matrices and an algorithm to use these matrices in pattern
recognition. Hit-miss matrices are templates that can be moved over
part of an input pattern to check for a 'match'. These matrices are
evolved using a 2-dimensional genetic algorithm, while the algorithms
controlling the templates are evolved using GP. The approach is
applied to the problem of digit recognition, and is found to be
successful at discovering individuals that which can recognize very
low resolution digits. Possibilities for expansion into a full-size
character recognition system are discussed.
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