LEADER 01823nam0 2200385 i 450 
001 SUN0114646
005 20180209090644.2
010   $d0.00
017 70$2N$a978-3-319-48814-1
100   $a20180208d2016       |0engc50      ba
101   $aeng
102   $aCH
105   $a||||    |||||
200 1 $a*Dynamic optimization$edeterministic and stochastic models$fKarl Hinderer, Ulrich Rieder, Michael Stieglitz
205   $a[Cham] : Springer, 2016
210   $aXXII$d530 p.$cill. ; 24 cm
215   $aPubblicazione in formato elettronico
410  1$1001SUN0024506$12001 $a*Universitext$1210  $aBerlin$cSpringer.
606   $a93E20$xOptimal stochastic control [MSC 2020]$2MF$3SUNC019946
606   $a90B10$xDeterministic network models in operations research [MSC 2020]$2MF$3SUNC021354
606   $a90-XX$xOperations research, mathematical programming [MSC 2020]$2MF$3SUNC025650
606   $a60J20$xApplications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) [MSC 2020]$2MF$3SUNC029367
606   $a90C40$xMarkov and semi-Markov decision processes [MSC 2020]$2MF$3SUNC033686
606   $a90C39$xDynamic programming [MSC 2020]$2MF$3SUNC033782
620   $aCH$dCham$3SUNL001889
700  1$aHinderer$b, Karl$3SUNV088702$0755886
701  1$aRieder$b, Ulrich$3SUNV088703$0512174
701  1$aStieglitz$b, Michael$3SUNV088704$0755887
712   $aSpringer$3SUNV000178$4650
801   $aIT$bSOL$c20201026$gRICA
856 4 $uhttp://dx.doi.org/10.1007/978-3-319-48814-1
912   $aSUN0114646
950   $aBIBLIOTECA CENTRO DI SERVIZIO SBA$d15CONS      SBA EBOOK 2208                      $e15EB 2208              20180208            
996   $aDynamic optimization$91523279
997   $aUNICAMPANIA