000 03341nam a22005175i 4500
001 978-1-4614-6983-4
003 DE-He213
005 20140220082827.0
007 cr nn 008mamaa
008 130413s2013 xxu| s |||| 0|eng d
020 _a9781461469834
_9978-1-4614-6983-4
024 7 _a10.1007/978-1-4614-6983-4
_2doi
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aCosta, Oswaldo Luiz do Valle.
_eauthor.
245 1 0 _aContinuous Average Control of Piecewise Deterministic Markov Processes
_h[electronic resource] /
_cby Oswaldo Luiz do Valle Costa, Francois Dufour.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXII, 116 p. 2 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Mathematics,
_x2191-8198
520 _aThe intent of this book is to present recent results in the control theory for the long run average continuous control problem of piecewise deterministic Markov processes (PDMPs). The book focuses mainly on the long run average cost criteria and  extends to the PDMPs some well-known techniques related to discrete-time and continuous-time Markov decision processes, including the so-called ``average inequality approach'', ``vanishing discount technique'' and ``policy iteration algorithm''. We believe that what is unique about our approach is that, by using the special features of the PDMPs, we trace a parallel with the general theory for discrete-time Markov Decision Processes rather than the continuous-time case. The two main reasons for doing that is to use the powerful tools developed in the discrete-time framework and to avoid working with the infinitesimal generator associated to a PDMP, which in most cases has its domain of definition difficult to be characterized. Although the book is mainly intended to be a theoretically oriented text, it also contains some motivational examples. The book is targeted primarily for advanced students and practitioners of control theory. The book will be a valuable source for experts in the field of Markov decision processes. Moreover,  the book should be suitable for certain advanced courses or seminars. As  background, one needs an acquaintance with the theory of Markov decision processes and some knowledge of stochastic processes and modern analysis.  
650 0 _aMathematics.
650 0 _aSystems theory.
650 0 _aDistribution (Probability theory).
650 1 4 _aMathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aContinuous Optimization.
650 2 4 _aSystems Theory, Control.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aComplex Systems.
700 1 _aDufour, Francois.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461469827
830 0 _aSpringerBriefs in Mathematics,
_x2191-8198
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-6983-4
912 _aZDB-2-SMA
999 _c95813
_d95813