A swarm-based crossover operator for genetic programming

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A swarm-based crossover operator for genetic programming

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 10th annual conference on Genetic and evolutionary computation table of contents

Atlanta, GA, USA

SESSION: Genetic Programming Postes table of contents

Pages 1345-1346

Year of Publication: 2008

ISBN:978-1-60558-130-9

Authors

Tony White	Carleton University, Ottawa, ON, Canada
Amirali Salehi-Abari	Carleton University, Ottawa, ON, Canada

Sponsors

ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

Publisher

ACM New York, NY, USA

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ABSTRACT

A swarm-based improvement to Genetic Programming (GP) is described and tested on the domain of symbolic regression in this paper. The motivating idea is to keep all of the benefits of genetic programming such as crossover and fitness proportional selection within a population of candidate solutions. The improvement comes in using swarm-based ideas similar to Ant Colony Optimization (ACO) to improve the operation of the crossover operator. Statistically significant results are reported in support of the hypothesis that ACO-inspired crossover can improve GP.

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.

	1	Shan Y., McKay R., Essam D., Abbass H., A Survey of Probabilistic Model Building using Genetic Programming. Technical Report TR-ALAR-200510014, The Artificial Life and Adaptive Robotics Laboratory, School of Information Technology and Electrical Engineering, University of New South Wales, Australia, 2005.
	2	Hammad Majeed , Conor Ryan, Using context-aware crossover to improve the performance of GP, Proceedings of the 8th annual conference on Genetic and evolutionary computation, July 08-12, 2006, Seattle, Washington, USA [doi>10.1145/1143997.1144146]
	3	Riccardo Poli and William B. Langdon. On the search properties of different crossover operators in genetic programming. In Genetic Programming 1998: Proceedings of the 3rd Annual Conference, pages 293--301, University of Wisconsin, Madison, Wisconsin, USA, 22-25 July 1998. Morgan Kaufmann.