Grammar-based Genetic Programming: a survey

• Published in: Genetic programming and evolvable machines Vol. 11; no. 3-4; pp. 365 - 396
• Main Authors: McKay, Robert I., Hoai, Nguyen Xuan, Whigham, Peter Alexander, Shan, Yin, O’Neill, Michael
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.09.2010
• Subjects: Artificial Intelligence; Biomedical Engineering and Bioengineering; Compilers; Computer Science; Contributed Article; Electrical Engineering; Formalism; Genetics; Grammars; Interpreters; Mathematical models; Programming; Programming Languages; Programming Techniques; Representations; Software Engineering/Programming and Operating Systems; Strands; Surveying; Tree adjoining; Grammar; Context free; Genetic programming; Regular; Evolutionary computation
• ISSN: 1389-2576; 1573-7632
• DOI: 10.1007/s10710-010-9109-y

Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP). Practical grammar-based GP systems first appeared in the mid 1990s, and have subsequently become an important strand in GP research and applications. We trace their subsequent rise, surveying the various grammar-based formalisms that have been used in GP and discussing the contributions they have made to the progress of GP. We illustrate these contributions with a range of applications of grammar-based GP, showing how grammar formalisms contributed to the solutions of these problems. We briefly discuss the likely future development of grammar-based GP systems, and conclude with a brief summary of the field.