Stochastic Hillclimbing as a Baseline Method for Evaluating Genetic Algorithms

Juels, Ari, Wattenberg, Martin

Neural Information Processing Systems 

We investigate the effectiveness of stochastic hillclimbing as a baseline for the performance of genetic algorithms (GAs) as combinatorialevaluating In particular, we address two problems to whichfunction optimizers.

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