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007			cr nn 008mamaa
008			120811s2013 xxk| s |||| 0|eng d
020			_a9781447142850 _9978-1-4471-4285-0
024	7		_a10.1007/978-1-4471-4285-0 _2doi
050		4	_aTJ212-225
072		7	_aTJFM _2bicssc
072		7	_aTEC004000 _2bisacsh
082	0	4	_a629.8 _223
100	1		_aBhatnagar, S. _eauthor.
245	1	0	_aStochastic Recursive Algorithms for Optimization _h[electronic resource] : _bSimultaneous Perturbation Methods / _cby S. Bhatnagar, H.L. Prasad, L.A. Prashanth.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2013.
300			_aXVIII, 302 p. 12 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Control and Information Sciences, _x0170-8643 ; _v434
505	0		_aPart I: Introduction to Stochastic Recursive Algorithms -- Introduction -- Deterministic Algorithms for Local Search -- Stochastic Approximation Algorithms -- Part II: Gradient Estimation Schemes -- Kiefer-Wolfowitz Algorithm -- Gradient Schemes with Simultaneous Perturbation Stochastic Approximation -- Smoothed Functional Gradient Schemes -- Part III: Hessian Estimation Schemes -- Hessian Estimation with Simultaneous Perturbation Stochasti Approximation -- Smoothed Functional Hessian Schemes -- Part IV: Variations to the Basic Scheme -- Discrete Optimization -- Algorithms for Contrained Optimization -- Reinforcement Learning -- Part V: Applications -- Service Systems -- Road Traffic Control -- Communication Networks.
520			_aStochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms: • are easily implemented; • do not require an explicit system model; and • work with real or simulated data. Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix. The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.
650		0	_aEngineering.
650		0	_aSystem theory.
650		0	_aCalculus of variations.
650		0	_aControl engineering.
650	1	4	_aEngineering.
650	2	4	_aControl.
650	2	4	_aCalculus of Variations and Optimal Control; Optimization.
650	2	4	_aSystems Theory, Control.
700	1		_aPrasad, H.L. _eauthor.
700	1		_aPrashanth, L.A. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781447142843
830		0	_aLecture Notes in Control and Information Sciences, _x0170-8643 ; _v434
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4471-4285-0
912			_aZDB-2-ENG
942			_2Dewey Decimal Classification _ceBooks
999			_c43540 _d43540