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where M(t, t)is the number of individuals in  . If we take the ratio   , we have an indication of how close t comes to "extinction" relative to t'(in the sense that extinction occurs when the population produced by t becomes negligible relative to the population produced by t'). If we take the greatest lower bound of this ratio relative to some set of possible plans  , we have an indication of the worst that can happen to t in E, relative to at time t. Continuing in this vein we get the following criterion for ranking plans as to robustness over e: |
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In effect this criterion ranks plans according to how close they come to extinction under the most unfavorable conditions. |
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The fantastic variety of possible genotypes, the effects of epistasis, changing environments, and the difficulty of retaining adaptations while maintaining variability (genetic variance), all constitute difficulties which genetic processes must surmount. In terms of the  framework these are, respectively, problems of the large size of  , the nonlinearity and high dimensionality of µE,the nonstationarity of µE, and the mutual interference of search and exploitation. The framework enables the definition of concepts (chapters 4 and 5) which in turn (chapters 6 through 9) help explain how genetic processes meet these difficulties in times consistent with paleological and current biological observations. |
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Summarizing: |
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,populations of chromosomes represented, for example, by the set of distributions over the set of genotypes  . |
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W,genetic operators such as mutation, crossover, inversion, dominance modification, translocation, deletion, etc. |
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, reproductive plans combining duplication according to fitness with the application of genetic operators; for example, if each operator  is applied to individuals with a fixed probability pi, then the set of possible plans can be represented by the set |
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e, the set of possible fitness functions  , each perhaps stated as a function of combinations of coadapted sets. |
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