%0 Conference Paper %1 fry:2003:gecco %A Fry, Rodney %A Tyrrell, Andy %B Genetic and Evolutionary Computation -- GECCO-2003 %C Chicago %D 2003 %E Cantú-Paz, E. %E Foster, J. A. %E Deb, K. %E Davis, D. %E Roy, R. %E O'Reilly, U.-M. %E Beyer, H.-G. %E Standish, R. %E Kendall, G. %E Wilson, S. %E Harman, M. %E Wegener, J. %E Dasgupta, D. %E Potter, M. A. %E Schultz, A. C. %E Dowsland, K. %E Jonoska, N. %E Miller, J. %I Springer-Verlag %K algorithms, genetic poster programming, %P 1804--1805 %T Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme %V 2724 %X The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm being unable to find the global optimum. We present a new method of approximating the genetic similarity between two individuals using ancestry information. We define a new diversity-preserving selection scheme, based on standard tournament selection, which encourages genetically dissimilar individuals to undergo genetic operation. The new method is illustrated by assessing its performance in a well-known problem domain: algebraic symbolic regression. %@ 3-540-40603-4

@inproceedings{fry:2003:gecco, abstract = {The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm being unable to find the global optimum. We present a new method of approximating the genetic similarity between two individuals using ancestry information. We define a new diversity-preserving selection scheme, based on standard tournament selection, which encourages genetically dissimilar individuals to undergo genetic operation. The new method is illustrated by assessing its performance in a well-known problem domain: algebraic symbolic regression.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Chicago}, author = {Fry, Rodney and Tyrrell, Andy}, biburl = {https://www.bibsonomy.org/bibtex/256c893bae55d4790a8018f14c429d09f/brazovayeye}, booktitle = {Genetic and Evolutionary Computation -- GECCO-2003}, editor = {Cant{\'u}-Paz, E. and Foster, J. A. and Deb, K. and Davis, D. and Roy, R. and O'Reilly, U.-M. and Beyer, H.-G. and Standish, R. and Kendall, G. and Wilson, S. and Harman, M. and Wegener, J. and Dasgupta, D. and Potter, M. A. and Schultz, A. C. and Dowsland, K. and Jonoska, N. and Miller, J.}, interhash = {fa2f00ef9e6a0e8f0d1194b787c50317}, intrahash = {56c893bae55d4790a8018f14c429d09f}, isbn = {3-540-40603-4}, keywords = {algorithms, genetic poster programming,}, month = {12-16 July}, notes = {GECCO-2003. A joint meeting of the twelfth International Conference on Genetic Algorithms (ICGA-2003) and the eighth Annual Genetic Programming Conference (GP-2003)}, pages = {1804--1805}, publisher = {Springer-Verlag}, publisher_address = {Berlin}, series = {LNCS}, timestamp = {2008-06-19T17:39:52.000+0200}, title = {Enhancing the Performance of {GP} Using an Ancestry-Based Mate Selection Scheme}, volume = 2724, year = 2003 }