000			02014nam a2200289 i 4500
001			200761
003			ES-MaBCM
005			20230726062701.0
008			151126t2015 us||||| |||| 00| 0 eng d
020			_a978-1-4987-1239-2
021			_axx
035			_a(OCoLC)1124033644
040			_cES-MaBCM
100	1		_aBanks, David L. _9119449
245	1	0	_aAdversarial risk analysis _cDavid L. Banks, Jesús Ríos, David Ríos Insua
260			_aBoca Raton, Florida : _bCRC Press, _c2015
300			_aX, 214 p. _bil. _c24 cm
500			_aÍndice
504			_aBibliografía: p.199-207
520			_aFlexible Models to Analyze Opponent Behavior. A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. The book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent's goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities.
650	2	7	_aTeoría de juegos _960435
650		7	_aGestión de conocimientos _978566
650	2	7	_aTécnica de gestión _960418
700	1		_9119450 _aRíos, Jesús
700	1		_9119451 _aRíos Insua, David
942			_cBK _2udc
999			_c200761 _d200761