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Unformatted text preview: tes the average fitness of a schema, but schema proliferation depends on its value Approximating schema dynamics Approximation can be refined by taking into account the operators Schemas of long defining length are less likely to survive crossover Offspring are less likely to be instances of such schemas Schemas of higher order are less likely to survive mutation Effects can be used to bound the approximate rates at which schemas proliferate Implications Instances of short, low­order schemas whose average fitness tends to stay above the mean will increase exponentially Changing the semantics of the operators can change the selective pressures toward different types of schemas Theoretical Foundations Empirical observation GAs can work Goal Learn how to best use the tool Strategy Understand the dynamics of the model Develop performance metrics in order to quantify success Theoretical Foundations Issues surrounding the dynamics of the model What laws characterize the macroscopic behavior of GAs? How do microscopic events give rise to this macroscopic behavior? Theoretical Foundation Holland’s motivation Construct a theoretical framework for adaptive systems as seen in nature Apply this framework to the design of artificial adaptive sys...
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This note was uploaded on 04/05/2010 for the course CS 723 taught by Professor Sc during the Spring '10 term at Jaypee University IT.

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