LEADER 03671nam 22007335 450 001 9910483193203321 005 20251230064808.0 010 $a3-030-76928-3 024 7 $a10.1007/978-3-030-76928-4 035 $a(CKB)4100000011955124 035 $a(DE-He213)978-3-030-76928-4 035 $a(MiAaPQ)EBC6637783 035 $a(Au-PeEL)EBL6637783 035 $a(OCoLC)1256243932 035 $a(PPN)258866020 035 $a(EXLCZ)994100000011955124 100 $a20210604d2021 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModern Trends in Controlled Stochastic Processes$eTheory and Applications, V.III /$fedited by Alexey Piunovskiy, Yi Zhang 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (XII, 356 p. 67 illus., 42 illus. in color.) 225 1 $aEmergence, Complexity and Computation,$x2194-7295 ;$v41 311 08$a3-030-76927-5 327 $aAverage Cost Markov Decision Processes with Semi-Uniform Feller Transition Probabilities -- First Passage Exponential Optimality Problem for Semi-Markov Decision Processes -- Controlled Random Walk: Conjecture and Counter-Example -- Optimal Stopping Problems for a Family of Continuous-Time Markov Processes -- Control of Continuous-Time Markov Jump Linear Systems with Partial Information. 330 $aThis book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this bookappealing and a valuable reference. . 410 0$aEmergence, Complexity and Computation,$x2194-7295 ;$v41 606 $aDynamics 606 $aNonlinear theories 606 $aEngineering$xData processing 606 $aComputational intelligence 606 $aNonlinear Optics 606 $aStochastic analysis 606 $aApplied Dynamical Systems 606 $aData Engineering 606 $aComputational Intelligence 606 $aNonlinear Optics 606 $aStochastic Analysis 615 0$aDynamics. 615 0$aNonlinear theories. 615 0$aEngineering$xData processing. 615 0$aComputational intelligence. 615 0$aNonlinear Optics. 615 0$aStochastic analysis. 615 14$aApplied Dynamical Systems. 615 24$aData Engineering. 615 24$aComputational Intelligence. 615 24$aNonlinear Optics. 615 24$aStochastic Analysis. 676 $a629.8312 676 $a629.8312 702 $aPiunovskiy$b Alexey 702 $aZhang$b Yi 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483193203321 996 $aModern Trends in Controlled Stochastic Processes$91972567 997 $aUNINA