Viewing the Problem from Different Angles: A New Diversity Measure Based on Angular Distances
Author(s) -
Henrik Berg
Publication year - 2009
Publication title -
journal of artificial evolution and applications
Language(s) - English
Resource type - Journals
eISSN - 1687-6237
pISSN - 1687-6229
DOI - 10.1155/2009/896595
Subject(s) - measure (data warehouse) , diversity (politics) , population , local optimum , computer science , evolutionary biology , mathematics , artificial intelligence , biology , data mining , sociology , demography , political science , law
It is commonly believed that diversity is crucial for an evolutionary system to succeed, especially when the problem to be solved contains local optima from which the population cannot easily escape. There exist numerous methods to measure population diversity, but none of these have been shown to be consistently useful. In this paper, a new diversity measure is introduced, and it is shown that high diversity according to this new measure generally leads to a more successful overall evolution in most of the cases considered.
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