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978-3-030-88398-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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https://doi.org/10.1007/978-3-030-88396-6Optimization; Algorithms; Decision Making; Control; Automation

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Introduction,Methods and algorithms for learning decision sequences in a repetitive process can be helpful in achieving optimal results under certain constraints.

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Basic Notions and Notations,This chapter aims to introduce basic notions and the relationships between them. In particular, concepts of repetitive processes, decisions and their constraints as well as loss (goal) functions are discussed.

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Learning Decision Sequences and Policies for Repetitive Processes,Learning is an inherent ability common to human beings. and animals. Learning in a broad sense is a very complicated phenomenon, involving physiological, social and psychological aspects, among others. These aspects are far beyond the scope of this book.