國立虎尾科技大學 |

Decision Making: Uncertainty, Imperfection, Deliberation and Scalability

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Decision Making: Uncertainty, Imperfection, Deliberation and Scalability/ edited by Tatiana V. Guy, Miroslav Kárný, David H. Wolpert.
其他作者:	Guy, Tatiana V.
面頁冊數:	XII, 184 p. 41 illus., 13 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-319-15144-1
ISBN:	9783319151441

Decision Making: Uncertainty, Imperfection, Deliberation and Scalability
Decision Making: Uncertainty, Imperfection, Deliberation and Scalability[electronic resource] /edited by Tatiana V. Guy, Miroslav Kárný, David H. Wolpert. - 1st ed. 2015. - XII, 184 p. 41 illus., 13 illus. in color.online resource. - Studies in Computational Intelligence,5381860-949X ;. - Studies in Computational Intelligence,564.

Bayesian 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.

This 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.

ISBN: 9783319151441

Standard No.: 10.1007/978-3-319-15144-1doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Decision Making: Uncertainty, Imperfection, Deliberation and Scalability
LDR:03133nam a22004095i 4500 001 960880
003 DE-He213
005 20200630072823.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319151441 $9 978-3-319-15144-1
024 7 $a 10.1007/978-3-319-15144-1 $2 doi
035 $a 978-3-319-15144-1
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Decision Making: Uncertainty, Imperfection, Deliberation and Scalability $h [electronic resource] / $c edited by Tatiana V. Guy, Miroslav Kárný, David H. Wolpert.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XII, 184 p. 41 illus., 13 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Computational Intelligence, $x 1860-949X ; $v 538
505 0 $a Bayesian 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 $a This 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 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Guy, Tatiana V. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1066502
700 1 $a Kárný, Miroslav. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1066503
700 1 $a Wolpert, David H. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 888724
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319151458
776 0 8 $i Printed edition: $z 9783319151434
776 0 8 $i Printed edition: $z 9783319350202
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-3-319-15144-1
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)