Attribute grammar evolution
EntityUAM. Departamento de Ingeniería Informática
PublisherSpringer Berlin Heidelberg
10.1007/11499305_19Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired Approach: First International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Spain, June 15-18, 2005, Proceedings. Part II. Lecture Notes in Computer Science, Volumen 3562. Springer, 2005. 182-191.
ISSN0302-9743 (print); 1611-3349 (online)
ISBN978-3-540-26319-7 (print); 978-3-540-31673-2 (online)
SubjectsComputation by Abstract Devices; Algorithm Analysis and Problem Complexity; Artificial Intelligence; Pattern Recognition; Evolutionary Biology; Image Processing; Computer Vision; Informática
NoteThe final publication is available at Springer via http://dx.doi.org/10.1007/11499305_19
Proceedings of First International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005
Rights© Springer-Verlag Berlin Heidelberg 2005
This paper describes Attribute Grammar Evolution (AGE), a new Automatic Evolutionary Programming algorithm that extends standard Grammar Evolution (GE) by replacing context-free grammars by attribute grammars. GE only takes into account syntactic restrictions to generate valid individuals. AGE adds semantics to ensure that both semantically and syntactically valid individuals are generated. Attribute grammars make it possible to semantically describe the solution. The paper shows empirically that AGE is as good as GE for a classical problem, and proves that including semantics in the grammar can improve GE performance. An important conclusion is that adding too much semantics can make the search difficult.
Google Scholar:Cruz Echeandía, Marina de la - Ortega de la Puente, Alfonso - Alfonseca, Manuel
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