000 03515nam a22004695i 4500
001 978-3-642-24647-0
003 DE-He213
005 20140220083303.0
007 cr nn 008mamaa
008 111112s2012 gw | s |||| 0|eng d
020 _a9783642246470
_9978-3-642-24647-0
024 7 _a10.1007/978-3-642-24647-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aGuy, Tatiana Valentine.
_eeditor.
245 1 0 _aDecision Making with Imperfect Decision Makers
_h[electronic resource] /
_cedited by Tatiana Valentine Guy, Miroslav Kárný, David H. Wolpert.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aXIV, 198p. 50 illus., 39 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 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v28
505 0 _a1 Bounded Rationality in Multiagent Systems Using Decentralized Metareasoning -- 2 On Support of Imperfect Bayesian Participants -- 3 Trading value and information in MDPs -- 4 Game theoretic modeling of pilot behavior during mid-air encounters -- 5 Scalable Negotiation Protocol based on Issue-Grouping for Highly Nonlinear Situation -- 6 The Social Ultimatum Game -- 7 Neuroheuristics of Decision Making: from neuronal activity to EEG.
520 _aPrescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, little research has been done from the perspective of computer science and associated disciplines like machine learning, information theory and neuroscience. This book is a major contribution to such research. Some of the particular topics addressed include: • How should we formalise rational decision making of a single imperfect decision maker? • Does the answer change for a system of imperfect decision makers? • Can we extend existing prescriptive theories for perfect decision makers to make them useful for imperfect ones? • How can we exploit the relation of these problems to the control under varying and uncertain resources constraints as well as to the problem of the computational decision making? • What can we learn from natural, engineered, and social systems to help us address these issues?
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aKárný, Miroslav.
_eeditor.
700 1 _aWolpert, David H.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642246463
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v28
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-24647-0
912 _aZDB-2-ENG
999 _c102316
_d102316