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Titlebook: Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains; Xi-Ren Cao Book 2021 The Author(s), under exclusive license to Spring

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书目名称Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains
编辑Xi-Ren Cao
视频video
概述Presents a comprehensive methodology for the performance optimization of time-nonhomogeneous Markov chains.Introduces the concept of confluencity, showing how it is fundamental to performance optimiza
丛书名称SpringerBriefs in Electrical and Computer Engineering
图书封面Titlebook: Foundations of Average-Cost Nonhomogeneous Controlled Markov Chains;  Xi-Ren Cao Book 2021 The Author(s), under exclusive license to Spring
描述.This Springer brief addresses the challenges encountered in the study of  the optimization of time-nonhomogeneous Markov chains. It develops new insights and new methodologies for systems in which concepts such as stationarity, ergodicity, periodicity and connectivity do not apply...This brief introduces the novel concept of confluencity and applies a relative optimization approach. It develops a comprehensive theory for optimization of the long-run average of time-nonhomogeneous Markov chains. The book shows that confluencity is the most fundamental concept in optimization, and that relative optimization is more suitable for treating the systems under consideration than standard ideas of dynamic programming. Using confluencity and relative optimization, the author classifies states as confluent or branching and shows how the under-selectivity issue of the long-run average can be easily addressed, multi-class optimization implemented, and Nth biases and Blackwell optimality conditions derived. These results are presented in a book for the first time and so may enhance the understanding of optimization and motivate new research ideas in the area..
出版日期Book 2021
关键词Markov Decision Processes; Blackwell Optimality; Branching States; Confluencity; Multi-Class Optimizatio
版次1
doihttps://doi.org/10.1007/978-3-030-56678-4
isbn_softcover978-3-030-56677-7
isbn_ebook978-3-030-56678-4Series ISSN 2191-8112 Series E-ISSN 2191-8120
issn_series 2191-8112
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2021
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