Grammatical Evolution: A Steady State approach


We describe a Genetic Algorithm that can evolve complete programs. Using a variable length linear genome to govern the mapping of a Backus Naur Form grammar definition to a program, expressions and programs of arbitrary complexity may be evolved. Our system, Grammatical Evolution, has been applied to problems such as a Symbolic Regression problem, and finding Trigonometric Identities. In this paper we describe how we applied GE to a Symbolic Integration problem, that being finding a function which is an integral of Cos(X)+2X+1. We also show how a Steady State selection mechanism was found to improve the performance of Grammatical Evolution.

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@inproceedings{Ryan1998GrammaticalEA, title={Grammatical Evolution: A Steady State approach}, author={Conor Ryan and Michael O ' Neill}, year={1998} }