000			03927nam a22004935i 4500
001			978-3-642-36406-8
003			DE-He213
005			20200421111839.0
007			cr nn 008mamaa
008			130202s2013 gw | s |||| 0|eng d
020			_a9783642364068 _9978-3-642-36406-8
024	7		_a10.1007/978-3-642-36406-8 _2doi
050		4	_aQ342
072		7	_aUYQ _2bicssc
072		7	_aCOM004000 _2bisacsh
082	0	4	_a006.3 _223
245	1	0	_aDecision Making and Imperfection _h[electronic resource] / _cedited by Tatiana V. Guy, Miroslav Karny, David Wolpert.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_aXV, 187 p. 72 illus., 24 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v474
505	0		_aDynamic Bayesian Combination of Multiple Imperfect Classifiers -- Distributed Decision Making by Categorically-Thinking Agents -- Automated Preference Elicitation for Decision Making -- Counter-Factual Reinforcement Learning: How To Model Decision-Makers that Anticipate the Future -- Effect of Emotion and Personality on Deviation from Purely Rational Decision-Making -- An Adversarial Risk Analysis Model for an Autonomous Imperfect Decision Agent.
520			_aDecision making (DM) is ubiquitous in both natural and artificial systems. The decisions made often differ from those recommended by the axiomatically well-grounded normative Bayesian decision theory, in a large part due to limited cognitive and computational resources of decision makers (either artificial units or humans). This state of a airs is often described by saying that decision makers are imperfect and exhibit bounded rationality. The neglected influence of emotional state and personality traits is an additional reason why normative theory fails to model human DM process.   The book is a joint effort of the top researchers from different disciplines to identify sources of imperfection and ways how to decrease discrepancies between the prescriptive theory and real-life DM. The contributions consider:   �          how a crowd of imperfect decision makers outperforms experts' decisions;   �          how to decrease decision makers' imperfection by reducing knowledge available;   �          how to decrease imperfection via automated elicitation of DM preferences;   �          a human's limited willingness to master the available decision-support tools as an additional source of imperfection;   �          how the decision maker's emotional state influences the rationality;  a DM support of edutainment robot based on its system of values and respecting emotions.   The book will appeal to anyone interested in the challenging topic of DM theory and its applications. .
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650		0	_aComputational intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
700	1		_aGuy, Tatiana V. _eeditor.
700	1		_aKarny, Miroslav. _eeditor.
700	1		_aWolpert, David. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642364051
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v474
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-36406-8
912			_aZDB-2-ENG
942			_cEBK
999			_c55479 _d55479