Cited By
View all- Huang ZMei YZhang FZhang MWagner M(2022)Graph-based linear genetic programmingProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528730(955-963)Online publication date: 8-Jul-2022
Caching for parallel linear genetic programming
Pages 201 - 202
Abstract
Parallel Linear Genetic Programming (PLGP) is an exciting new approach to Linear Genetic Programming (LGP) which decreases building block disruption and significantly improves performance by the introduction of a parallel architecture. We introduce a caching algorithm for PLGP which exploits this parallel architecture to avoid the majority of instruction executions. This allows PLGP programs to be executed an order of magnitude faster than LGP programs with an equal number of instructions.
References
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W. Banzhaf, P. Nordin, R. E. Keller, and F. D. Francone. Genetic Programming: An Introduction on the Automatic Evolution of computer programs and its Applications. Morgan Kaufmann Publishers, 1998.
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C. Downey and M. Zhang. Parallel linear genetic programming. In EuroGP, volume 6621, pages 178--189, 2011.
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B. E. Eskridge and D. F. Hougen. Memetic crossover for genetic programming: Evolution through imitation. In Genetic and Evolutionary Computation - GECCO, Part II, volume 3103 of Lecture Notes in Computer Science, pages 459--470. Springer-Verlag, 2004.
Index Terms
- Caching for parallel linear genetic programming
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July 2011
1548 pages
Copyright © 2011 Authors.
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Association for Computing Machinery
New York, NY, United States
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Published: 12 July 2011
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Cited By
View all- Huang ZMei YZhang FZhang MWagner M(2022)Graph-based linear genetic programmingProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528730(955-963)Online publication date: 8-Jul-2022
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