| Algebraic simplification of GP programs during evolution |
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Genetic And Evolutionary Computation Conference
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Proceedings of the 8th annual conference on Genetic and evolutionary computation
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Seattle, Washington, USA
SESSION: Genetic programming: papers
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Pages: 927 - 934
Year of Publication: 2006
ISBN:1-59593-186-4
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Authors
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Phillip Wong
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Victoria University of Wellington, Wellington, New Zealand
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Mengjie Zhang
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Victoria University of Wellington, Wellington, New Zealand and M&E College, Agricultural University of Hebei, Baoding, China
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Downloads (6 Weeks): 3, Downloads (12 Months): 47, Citation Count: 4
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ABSTRACT
Program bloat is a fundamental problem in the field of Genetic Programming (GP). Exponential growth of redundant and functionally useless sections of programs can quickly overcome a GP system, exhausting system resources and causing premature termination of the system before an acceptable solution can be found. Simplification is an attempt to remove such redundancies from programs. This paper looks at the effects of applying an algebraic simplification algorithm to programs during the GP evolution. The GP system with the simplification is examined and compared to a standard GP system on four regression and classification problems of varying difficulty. The results suggest that the GP system employing a simplification component can achieve superior efficiency and effectiveness to the standard system on these problems.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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