In isotropic Gaussian random field fitness landscapes the expected number of local optima is determined by the correlation of fitness effects, with modularity increasing and locus heterogeneity decreasing the count.
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Epistatic strength, modularity, and locus heterogeneity shape the number of local optima in fitness landscapes
In isotropic Gaussian random field fitness landscapes the expected number of local optima is determined by the correlation of fitness effects, with modularity increasing and locus heterogeneity decreasing the count.