By Matthias Schmidt

ISBN-10: 9533071737

ISBN-13: 9789533071732

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This algorithm directly uses a generative context-free grammar (CFG) to generate structures in an arbitrary language defined by that grammar. A genetic algorithm is used to direct the structure generation. The usage of a context-free grammar to generate a solution ensures that a solution is always syntactically correct. It also enables to precisely and flexibly define the form of a solution without the need to alter the algorithm implementation. Fig. 1. Production rules of grammar for generating arithmetic expressions In grammatical evolution each individual in the population is represented by a sequence of rules of a defined (context-free) grammar.

Gene Duplication to Enable Genetic Programming to Concurrently Evolve Both the Architecture and Work-Performing Steps of a Computer Program, IJCAI- Automatic Generation of Programs 35 95 – Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Vol. 1, pp. R. et al (2003). Genetic Programming IV: Routine Human-Competitive Machine Intelligence. , ISBN 978-1402074462, USA Laddad, R. (2009). Aspectj in Action: Enterprise AOP with Spring Applications, Manning Publications, ISBN 978-1933988054, Greenwich, Connecticut, USA Mitchell, M.

Production rules define the laws under which non-terminals are translated to terminals. Production rules are key part of the grammar definition as they actually define the structure of the generated solution (O’Neill & Ryan, 2003). We will demonstrate the principle of grammatical evolution and the backward processing algorithm on generating algebraic expressions. The grammar we can use to generate arithmetic expressions is defined by equations (1) – (3); for brevity, the production rules are shown separately in BNF notation on Figure 1 (Ošmera & Popelka, 2006).

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