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005 20151013141915.0
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008 141127s2015 gw | s |||| 0|eng d
020 _a9783319118338
_9978-3-319-11833-8
024 7 _a10.1007/978-3-319-11833-8
_2doi
050 4 _aHD30.23
072 7 _aKJT
_2bicssc
072 7 _aKJMD
_2bicssc
072 7 _aBUS049000
_2bisacsh
082 0 4 _a658.40301
_223
100 1 _aLozovanu, Dmitrii.
_eauthor.
245 1 0 _aOptimization of Stochastic Discrete Systems and Control on Complex Networks
_h[electronic resource] :
_bComputational Networks /
_cby Dmitrii Lozovanu, Stefan Pickl.
260 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _aXIX, 400 p. 54 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Computational Management Science,
_x1388-4301 ;
_v12
505 0 _aDiscrete stochastic processes, numerical methods for Markov chains and polynomial time algorithms -- Stochastic optimal control problems and Markov decision processes with infinite time horizon -- A game-theoretical approach to Markov decision processes, stochastic positional games and multicriteria control models -- Dynamic programming algorithms for finite horizon control problems and Markov decision processes.
520 _aThis book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book’s final chapter is devoted to finite horizon stochastic control problems and Markov decision processes. The algorithms developed represent a valuable contribution to the important field of computational network theory.
650 0 _aEconomics.
650 0 _aComputer software.
650 0 _aMathematical optimization.
650 0 _aOperations research.
650 1 4 _aEconomics/Management Science.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aOptimization.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aDiscrete Optimization.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
700 1 _aPickl, Stefan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319118321
830 0 _aAdvances in Computational Management Science,
_x1388-4301 ;
_v12
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-11833-8
912 _aZDB-2-SBE
942 _2ddc
_cEBOOK
999 _c3151
_d3151