| 000 | 03486nam a22003615i 4500 | ||
|---|---|---|---|
| 001 | 103976 | ||
| 003 | DE-He213 | ||
| 005 | 20240111050148.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 150209s2015 gw | s |||| 0|eng d | ||
| 020 | _a9783319151441 | ||
| 024 | 7 |
_a10.1007/978-3-319-15144-1 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC |
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| 050 | 4 | _aHD30.213 2015 EB | |
| 245 | 1 | 0 |
_aDecision Making: Uncertainty, Imperfection, Deliberation and Scalability _cedited by Tatiana V. Guy, Miroslav Kárný, David H. Wolpert. |
| 264 | 1 |
_aCham _bSpringer International Publishing _c2015 |
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| 300 | _a1 recurso en línea (XII, 184 páginas 41 ilustraciones, 13 ilustraciones a color.) | ||
| 490 | 0 |
_aStudies in Computational Intelligence _x1860-949X ; _v538 |
|
| 505 | 0 | _aBayesian Methods for Intelligent Task Assignment in Crowdsourcing Systems -- Designing Societies of Robots -- On the Origins of Imperfection and Apparent Non-Rationality -- Lasso Granger Causal Models: Some Strategies and their Efficiency for Gene Expression Regulatory Networks -- Cooperative Feature Selection in Personalized Medicine -- Imperfect Decision Making and Risk Taking are affected by Personality. | |
| 520 | 3 | _aThis volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selfish decision makers. The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making. Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems. In particular, analyses and experiments are presented which concern: • task allocation to maximize "the wisdom of the crowd"; • design of a society of "edutainment" robots who account for one anothers' emotional states; • recognizing and counteracting seemingly non-rational human decision making; • coping with extreme scale when learning causality in networks; • efficiently incorporating expert knowledge in personalized medicine; • the effects of personality on risky decision making. The volume is a valuable source for researchers, graduate students and practitioners in machine learning, stochastic control, robotics, and economics, among other fields. | |
| 650 | 7 |
_aToma de decisiones _2embne _9141176 |
|
| 650 | 7 |
_aInteligencia artificial _2embne _9413115 |
|
| 700 | 1 |
_aGuy, Tatiana V. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
| 700 | 1 |
_aKárný, Miroslav. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n83215081 _1http://viaf.org/viaf/46822694/ |
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| 700 | 1 |
_aWolpert, David H. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _0http://id.loc.gov/authorities/names/n94104935 _1http://viaf.org/viaf/108518014/ |
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| 776 | 0 | 8 |
_iEdición impresa: _z9783319151458 |
| 776 | 0 | 8 |
_iEdición impresa: _z9783319151434 |
| 776 | 0 | 8 |
_iEdición impresa: _z9783319350202 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-15144-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 490 | 0 | _aEngineering (Springer-11647) | |
| 988 | _aEBSPRINGER_2018 | ||
| 998 |
_b06/2019 _dz _ek _feng _ggw _h0 |
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| 999 |
_c103976 _d103976 _x1 |
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