Convergence is a necessary part of any successful GP run, but is also a great weakness due to material lost through the hemorrhage of genetic content through the established evolutionary dynamics. This chapter examines the phenomenon of convergence commonly observed in evolutionary systems before introducing a number of functionally distinct mechanisms are analysed and tested with respect to their ability to modulate the loss of potentially useful genetic content. Each of these methods use little or no explicit measurements to calculate diversity, and we show that they can have a dramatic effect on empirical performance of GP.
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Murphy, G., Ryan, C. (2008). Manipulation of Convergence in Evolutionary Systems. In: Riolo, R., Soule, T., Worzel, B. (eds) Genetic Programming Theory and Practice V. Genetic and Evolutionary Computation Series. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-76308-8_3
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DOI: https://doi.org/10.1007/978-0-387-76308-8_3
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