Abstract
A limit theorem is established for the asymptotic state of a Markov chain arising from an iterative renormalization. The limit theorem is illustrated in applications to the theory of random search and in probabilistic models for descent algorithms. Some special cases are also noted where exact distributional results can be obtained.
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