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General Schema Theory for Genetic Programming with Subtree ...

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R. Poli and N. F. McPhee<br />

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�<br />

� �<br />

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��¥ £�§���§������ �<br />

and<br />

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§ �<br />

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� ¥�� � ����¥ £¨§������ � ¥�� � ����¥ £�§���§������<br />

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�<br />

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� ��� � ��� � � ��� �<br />

If non-empty, the sets ��¥ �<br />

�<br />

are (or can be represented<br />

£¨§������<br />

by) fixed-size-and-shape schemata. So, the theorem expresses the total transmission<br />

probability £ of only using the selection probabilities of a set of lower- (or same-) order<br />

schemata.<br />

5 Applications and Specialisations<br />

In this section we show how the theory can be specialised to obtain schema theorems<br />

<strong>for</strong> specific crossover operators, and we illustrate how it can be used to obtain other<br />

general theoretical results, such as an exact definition of effective fitness and a sizeevolution<br />

equation <strong>for</strong> GP <strong>with</strong> subtree-swapping crossover.<br />

5.1 Macroscopic Exact <strong>Schema</strong> Theorem <strong>for</strong> GP <strong>with</strong> Standard Crossover<br />

Let us specialise Theorem 2 to standard crossover (Koza, 1992). For simplicity we will<br />

do this <strong>for</strong> the case in which the crossover points are selected uni<strong>for</strong>mly at random.<br />

In order to use the theorem we need to check whether standard crossover is<br />

node invariant, i.e. whether it is true � ¥ ��§���� ��� § ��� ����� ¥ ��§���� ��¥���� ��§ ��¥���� ��� that . The<br />

notion of name function introduced in Part I is applicable to any tree, including<br />

schemata. If � is an order-0 schema (i.e. a program � ¥�� §���§ � ��� ��� shape) exactly when<br />

§���� is in the schema. It then follows that if ¥�� � is a program and ��¥�� is its shape, �<br />

¥�� §���§ � ��� ��� if and only if � ¥�� §���§ ��¥�� ����� ��� . Also, clearly � ¥�� ����� ¥���¥�� ��� . So, using<br />

�<br />

and � to represent the coordinates � ¥���� � � and §�� ¥���� � � , respectively, the expression of<br />

§��<br />

� ¥���� §�� � § ��� §�� � � ��� § ��� � in Part I can be trans<strong>for</strong>med as follows<br />

�������������<br />

� ����������� � ¥ ��§���� � � § � � ���<br />

So, we can replace � ¥ ��§���� �<br />

�<br />

§ �<br />

�<br />

¥ � ¥ ��§ ��� ��� ����� � ¥ � ¥ ��§ ��� ��� �����<br />

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¥���� ��� ¥���� � �<br />

� ¥���¥�� � ����� ¥���¥�� � ���<br />

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������������� � ¥ ��§���� ��¥���� ��§ ��¥���� �����<br />

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¥ � ¥ ��§ ��¥���� ����� ����� � ¥ � ¥ ��§ ��¥���� ����� �����<br />

�<br />

� in Equation 10 <strong>with</strong> the expression<br />

� ¥ � ¥ ��§ �<br />

obtaining, after appropriate simplification:<br />

�<br />

����� � ¥ � ¥ ��§ � ���<br />

¥��<br />

�<br />

��� ¥��<br />

�<br />

� �<br />

�<br />

����� ���<br />

Theorem 3 (Macroscopic Exact GP <strong>Schema</strong> Theorem <strong>for</strong> Standard Crossover) The total<br />

transmission probability <strong>for</strong> a fixed-size-and-shape GP schema £ under standard crossover<br />

<strong>with</strong> uni<strong>for</strong>m selection of crossover points is given by Equation 2 <strong>with</strong><br />

� xo ¥ £¨§�©�������� � �<br />

� ¥��<br />

� �<br />

¥��<br />

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� ¥���¥ £¨§������ � �<br />

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§<br />

§�©���� ¥���¥ £¨§���§������ �<br />

�<br />

�<br />

� �<br />

§�©���� (12)<br />

18 Evolutionary Computation Volume ?, Number ?<br />

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