Abstract
In this paper we first review the main results
obtained in the theory of schemata in Genetic
Programming (GP) emphasising their strengths and
weaknesses. Then we propose a new, simpler definition
of the concept of schema for GP which is quite close to
the original concept of schema in genetic algorithms
(GAs). Along with a new form of crossover, one-point
crossover, and point mutation this concept of schema
has been used to derive an improved schema theorem for
GP which describes the propagation of schemata from one
generation to the next. In the paper we discuss this
result and show that our schema theorem is the natural
counterpart for GP of the schema theorem for GAs, to
which it asymptotically converges.
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