Decision making : uncertainty, imperfection, deliberation and scalability /

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Bibliographic Details
Imprint:Cham : Springer, 2015.
©2015
Description:1 online resource (xii, 184 pages) : illustrations (some color).
Language:English
Series:Studies in Computational Intelligence, 1860-949X ; volume 538
Studies in computational intelligence ; 538.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11091864
Hidden Bibliographic Details
Other authors / contributors:Guy, Tatiana Valentine, editor.
Kárný, M., editor.
Wolpert, David H., editor.
ISBN:9783319151441
3319151444
9783319151434
3319151436
9783319151434
Digital file characteristics:text file PDF
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed February 20, 2015).
Summary:This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selƠ̐ℓsh 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: ℓ́Ø task allocation to maximize ℓ́ℓthe wisdom of the crowdℓ́ℓ; ℓ́Ø design of a society of ℓ́ℓedutainmentℓ́ℓ robots who account for one anothersℓ́ℓ emotional states; ℓ́Ø recognizing and counteracting seemingly non-rational human decision making; ℓ́Ø coping with extreme scale when learning causality in networks; ℓ́Ø efƠ̐ℓciently incorporating expert knowledge in personalized medicine; ℓ́Ø 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 Ơ̐ℓelds.
Other form:Printed edition: 9783319151434
Standard no.:10.1007/978-3-319-15144-1

MARC

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504 |a Includes bibliographical references. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed February 20, 2015). 
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 selƠ̐ℓsh 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: ℓ́Ø task allocation to maximize ℓ́ℓthe wisdom of the crowdℓ́ℓ; ℓ́Ø design of a society of ℓ́ℓedutainmentℓ́ℓ robots who account for one anothersℓ́ℓ emotional states; ℓ́Ø recognizing and counteracting seemingly non-rational human decision making; ℓ́Ø coping with extreme scale when learning causality in networks; ℓ́Ø efƠ̐ℓciently incorporating expert knowledge in personalized medicine; ℓ́Ø 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 Ơ̐ℓelds. 
650 0 |a Decision making.  |0 http://id.loc.gov/authorities/subjects/sh85036199 
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