Location Independent Pattern Recognition using Genetic
Programming
Genetic Algorithms and Genetic Programming at Stanford
1995, Stanford Bookstore, Stanford, California, 94305-3079 USA, (11 December 1995)Abstract
This paper describes an application of genetic
programming. Programs able of recognising a pattern
independent of its location are evolved. Usually the
evolution of programs is controlled primarily by the
fitness evaluation function. This paper demonstrates
how genetic programming can be encouraged to evolve
programs with properties not being explicitly
considered in the fitness measure like location
independence. The measurements taken include the use of
automatically defined functions allowing the problem to
be decomposed into sub-functions, a special
implementation of iteration and carefully chosen
function and terminal sets. A main purpose was to
minimise the restrictions imposed on the solution, i.e.
giving the genetic programming as much freedom as
possible while still encouraging the desired
properties.