Abstract

The genetic programming (GP) paradigm is a functional approach to inductively forming programs. The use of natural selection based on a fitness function for reproduction of the program population has allowed many problems to be solved that require a non-fixed representation. Attempts to extend GP have focussed on typing the language to restrict crossover and to ensure legal programs are always created. We describe the use of a context free grammar to define the structure of the initial language and to direct crossover and mutation operators. The use of a grammar to specify structure in the hypothesis language allows a clear statement of inductive bias and control over typing. Modifying the grammar as the evolution proceeds is used as an example of learnt bias. This technique leads to declarative approaches to evolutionary learning, and allows fields such as incremental learning to be incorporated under the same paradigm. 1 Introduction The Genetic Programming paradigm (GP) has receive...

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