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001			278171
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007			cr nn 008mamaa
008			150903s2006 xxu| o |||| 0|eng d
020			_a9780387312798 _99780387312798
024	7		_a10.1007/b120940 _2doi
035			_avtls000330924
039		9	_a201509031112 _bVLOAD _c201405070501 _dVLOAD _c201401311356 _dstaff _c201401311220 _dstaff _y201401301157 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ295
100	1		_aChornei, Ruslan K. _eautor _9301575
245	1	0	_aControl of Spatially Structured Random Processes and Random Fields with Applications / _cby Ruslan K. Chornei, Hans Daduna, Pavel S. Knopov.
264		1	_aBoston, MA : _bSpringer US, _c2006.
300			_axiv, 262 páginas, _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aNonconvex Optimization and Its Applications, _x1571-568X ; _v86
500			_aSpringer eBooks
505	0		_aPrerequisites from the Theory of Stochastic Processes and Stochastic Dynamic Optimization -- Local Control of Discrete Time Interacting Markov Processes with Graph Structured State Space -- Sequential Stochastic Games with Distributed Players on Graphs -- Local Control of Continuous Time Interacting Markov and Semi-Markov Processes with Graph Structured State Space -- Connections with Optimization of Random Field in Different Areas.
520			_aThis book is devoted to the study and optimization of spatiotemporal stochastic processes, that is, processes which develop simultaneously in space and time under random influences. These processes are seen to occur almost everywhere when studying the global behavior of complex systems, including • physical and technical systems, • population dynamics, • neural networks, • computer and telecommunication networks, • complex production networks, • flexible manufacturing systems, • logistic networks and transportation systems, • environmental engineering, • climate modelling and prediction, • earth surface models. Classical stochastic dynamic optimization forms the framework of the book. Taken as a whole, the project undertaken in the book is to establish optimality or near-optimality for Markovian policies in the control of spatiotemporal Markovian processes. The authors apply this general principle to different frameworks of Markovian systems and processes. Depending on the structure of the systems and the surroundings of the model classes the authors arrive at different levels of simplicity for the policy classes which encompass optimal or nearly optimal policies. A set of examples accompanies the theoretical findings, and these examples should demonstrate some important application areas for the theorems discussed. Audience This book is intended for experts in applied mathematics, cybernetics, and in the theory of optimal control.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aDaduna, Hans. _eautor _9301576
700	1		_aKnopov, Pavel S. _eautor _9301577
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387304090
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/b120940 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c278171 _d278171