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008			220218s2022 sz | s |||| 0|eng d
020			_a9783030933173
024	7		_a10.1007/978-3-030-93317-3 _2doi
040			_aTR-AnTOB _beng _erda _cTR-AnTOB
041			_aeng
050		4	_aQA402.3
072		7	_aPBU _2bicssc
072		7	_aMAT005000 _2bisacsh
072		7	_aPBU _2thema
090			_aQA402.3EBK
100	1		_aMolloy, Timothy L. _eauthor. _0(orcid)0000-0002-6797-5617 _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aInverse Optimal Control and Inverse Noncooperative Dynamic Game Theory _h[electronic resource] : _bA Minimum-Principle Approach / _cby Timothy L. Molloy, Jairo Inga Charaja, Sören Hohmann, Tristan Perez.
250			_a1st ed. 2022.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2022.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aCommunications and Control Engineering, _x2197-7119
505	0		_aIntroduction -- Chapter 1. Discrete-Time Inverse Optimal Control -- Chapter 2. Continuous-Time Inverse Optimal Control -- Chapter 3. Inverse Noncooperative Dynamic Games -- Chapter 4. Inverse Noncooperative Differential Games -- Applications.
520			_aThis book presents a novel unified treatment of inverse problems in optimal control and noncooperative dynamic game theory. It provides readers with fundamental tools for the development of practical algorithms to solve inverse problems in control, robotics, biology, and economics. The treatment involves the application of Pontryagin's minimum principle to a variety of inverse problems and proposes algorithms founded on the elegance of dynamic optimization theory. There is a balanced emphasis between fundamental theoretical questions and practical matters. The text begins by providing an introduction and background to its topics. It then discusses discrete-time and continuous-time inverse optimal control. The focus moves on to differential and dynamic games and the book is completed by consideration of relevant applications. The algorithms and theoretical results developed in Inverse Optimal Control and Inverse Noncooperative Dynamic Game Theory provide new insights into information requirements for solving inverse problems, including the structure, quantity, and types of state and control data. These insights have significant practical consequences in the design of technologies seeking to exploit inverse techniques such as collaborative robots, driver-assistance technologies, and autonomous systems. The book will therefore be of interest to researchers, engineers, and postgraduate students in several disciplines within the area of control and robotics.
650		0	_aMathematical optimization.
650		0	_aCalculus of variations.
650		0	_aControl engineering.
650		0	_aMathematics—Philosophy.
650		0	_aSystem theory.
650		0	_aControl theory.
650	1	4	_aCalculus of Variations and Optimization.
650	2	4	_aControl and Systems Theory.
650	2	4	_aPhilosophy of Mathematics.
650	2	4	_aSystems Theory, Control .
653		0	_aControl theory -- Mathematical models
653		0	_aGame theory
700	1		_aInga Charaja, Jairo. _eauthor. _0(orcid)0000-0001-6554-9457 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aHohmann, Sören. _eauthor. _0(orcid)0000-0002-4170-1431 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aPerez, Tristan. _eauthor. _0(orcid)0000-0003-1486-2202 _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
830		0	_aCommunications and Control Engineering, _x2197-7119
856	4	0	_uhttps://doi.org/10.1007/978-3-030-93317-3 _3Springer eBooks _zOnline access link to the resource
942			_2lcc _cEBK