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Titlebook: Markov Processes and Controlled Markov Chains; Zhenting Hou,Jerzy A. Filar,Anyue Chen Book 20021st edition Kluwer Academic Publishers 2002

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发表于 2025-3-21 19:21:52 | 显示全部楼层 |阅读模式
书目名称Markov Processes and Controlled Markov Chains
编辑Zhenting Hou,Jerzy A. Filar,Anyue Chen
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图书封面Titlebook: Markov Processes and Controlled Markov Chains;  Zhenting Hou,Jerzy A. Filar,Anyue Chen Book 20021st edition Kluwer Academic Publishers 2002
描述.The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South American and Asian scholars..
出版日期Book 20021st edition
版次1
doihttps://doi.org/10.1007/978-1-4613-0265-0
isbn_softcover978-1-4613-7968-3
isbn_ebook978-1-4613-0265-0
copyrightKluwer Academic Publishers 2002
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Identifying ,-Processes with a Given Finite ,-Invariant Measurestate 0, which is accessible from .. Suppose that . admits a .-subinvariant measure . = (.., . ∈ . on .. We consider the problem of identifying all .-processes for which . is a .-invariant measure on ..
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Average Optimality for Adaptive Markov Control Processes with Unbounded Costs and Unknown Disturbanc one-stage costs. The processes evolve according to recursive equations ..+1 = .(.., ..,ξ.),. = 0, 1,…, with i.i.d. ℜ. — valued random vectors ξ. with unknown distribution. Assuming observability of ξ., we propose three different sets of conditions each of which allows us to prove average optimality of a type of adaptive control policies.
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Optimality Conditions for CTMDP with Average Cost Criterionion. We present a set of conditions that is weaker than those in [5, 11, 12, 14], and prove the existence of optimal stationary policies using the optimality inequality. Moreover, the theory is illustrated by two examples.
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Constrained Discounted Semi-Markov Decision ProcessesThis paper reduces problems on the existence and the finding of optimal policies for multiple criterion discounted SMDPs to similar problems for MDPs. We prove this reduction and illustrate it by extending to SMDPs several results for constrained discounted MDPs.
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978-1-4613-7968-3Kluwer Academic Publishers 2002
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