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Properties of fitness landscapes

One of the most important landscape properties is autocorrelation, a measure of similarity of fitnesses of neighboring points. Uncorrelated landscapes may have very dissimilar fitness values for adjacent points and are called rugged. Formally, for landscapes which are stationary (have the same mean, variance and autocorrelation throughout the space), autocorrelation is defined as [Pg.127]

Several types of autocorrelation are often used for landscapes. In several important papers, Weinberger and Stadler consider both autocorrelation between adjacent points along a random walk in the landscape and autocorrelation between points a given Hamming distance apart independent of any walk [67,77,78,82,83], Both definitions yield similar information about the landscape and can be computed from one another for stationary landscapes. Other types of autocorrelation are based on neighborhoods defined by complex mutation operations such as crossover [45-49,85], [Pg.128]

Quite often, a model is capable of producing all possible landscapes however, for the vast majority of landscapes, the probability of the model producing them is extremely low. The quality of a fitness landscape model is determined by how closely its landscape probabilities match those of the problem being considered. [Pg.129]


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