Abstract
A major goal of the previous chapters has been to enable a rigorous mathematical analysis of optimizer performance within a common space of optimization methods. Performance is not directly determined by how an optimization method chooses a particular point given a history; it arises as a consequence of the totality of decisions made by an optimization method over the course of time. Therefore, the search generators analyzed in the prior chapters must be connected to a method for generating complete history traces over the entire temporal index set.
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Lockett, A.J. (2020). Generating the Optimization Process. In: General-Purpose Optimization Through Information Maximization. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62007-6_9
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DOI: https://doi.org/10.1007/978-3-662-62007-6_9
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