Summary
Grammatical Evolution (GE) is a novel evolutionary algorithm that uses a genotype-to-phenotype mapping process where variable-length binary strings govern which production rules of a Backus Naur Form grammar are used to generate programs. This paper describes the Java GE project (jGE), which is an implementation of GE in the Java language, as well as some proof-of-concept experiments. The main idea behind the jGE Library is to create a framework for evolutionary algorithms which can be extended to any specific implementation such as Genetic Algorithms, Genetic Programming and Grammatical Evolution.
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References
Georgiou L, Teahan WJ (2006) jGE—A Java implementation of Grammatical Evolution. 10th WSEAS Int. Conf. on Systems, Athens, July
Ghanea-Hercock R (2003) Applied Evolutionary Algorithms in Java. New York, NY: Springer
jGE v0.1. (2006), Java GE (jGE) Official Web Site. School of Informatics, Univ. Wales, Bangor, U.K. http://www.informatics.bangor.ac.uk/~loukas/jge
Jikes 1.22. IBM Corp. (2004), USA: NY. http://jikes.sourceforge.net
Koza JR (1992) Genetic Programming: On the Programming of Computers by the Means of Natural Selection. Cambridge, MA: MIT Press
Koza JR (1994) Genetic Programming II: Automatic Discovery of Reusable Programs. Camb., MA: MIT Press
Mayr E (2002) What Evolution Is. London: Phoenix
Nicolau M (2006), libGE: Grammatical Evolution Library for version 0.26beta1, 3 March 2006. http://waldo.csisdmz.ul.ie/libGE/libGE.pdf
O’Neill M, Ryan C (1999) Evolving Multi-line Compilable C Programs. In: Proc. of the 2nd European Workshop on Genetic Prog., 1999, pp. 83–92
O’Neill, M, Ryan C (2001) Grammatical Evolution. IEEE Transactions on Evolutionary Computation 5(4), 349–358
O’Neill M, Ryan C (2003) Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. USA: Kluwer
O’Neill M, Ryan C, Nicolau M (2001) Grammar Defined Introns: An Investigation into Grammars, Introns, and Bias in Grammatical Evolution. In Proceedings of GECCO 2001
Paterson N, Livesey M (1997) Evolving caching algorithms in C by GP. In Genetic Programming 1997, pp. 262–267. MIT Press
Ryan C, Collins JJ, and O’Neill M (1998a) Grammatical Evolution: Evolving Programs for an Arbitrary Language. Lecture Notes in Comp. Sci. 1391. First European Workshop on Genetic Programming 1998
Ryan C, O’Neill M (1998) Grammatical Evolution: A Steady State Approach. In Proceedings of the 2nd Int. Workshop on Frontiers in Evolutionary Algorithms, 1998, pp. 419–423
Ryan C, O’Neill M, Collins JJ (1998b) Grammatical Evolution: Solving Trigonometric Identities. In Proceedings of Mendel 1998: 4th Int. Mendel Conf. on Genetic Algorithms, Optimisation Problems, Fuzzy Logic, Neural Networks, Rough Sets held in Brno, Czech Republic June 24-26 1998, pp. 111–119
Teahan WJ, Al-Dmour N, Tuff PG (2005) On thought, knowledge, evolution and search. In Proceedings of Computer Methods and Systems CMS’05 Conference held in Krakow, Poland, 14–16 November 2005
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Georgiou, L., Teahan, W.J. (2008). Experiments with Grammatical Evolution in Java. In: Cotta, C., Reich, S., Schaefer, R., Ligęza, A. (eds) Knowledge-Driven Computing. Studies in Computational Intelligence, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77475-4_4
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DOI: https://doi.org/10.1007/978-3-540-77475-4_4
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