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050 4 _aQ335
_b.R63 2016 EB
245 0 0 _aRobust Intelligence and Trust in Autonomous Systems
_cedited by Ranjeev Mittu, Donald Sofge, Alan Wagner, WF Lawless
260 _aBoston, MA
_bSpringer US
_c2016
300 _a1 recurso en línea (XII, 270 páginas)
_b89 ilustraciones, 64 ilustraciones en color
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
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505 0 _aIntroduction -- Towards modeling the behavior of autonomous systems and humans for trusted operations -- Learning trustworthy behaviors using an inverse trust metric.- The "Trust V"-Building and measuring trust in autonomous systems -- Big Data analytic paradigms-From principle component analysis to deep learning -- Artificial brain systems based on neural network discrete chaotic dynamics. Toward the development of conscious and rational robots -- Modeling and control of trust in human-robot collaborative manufacturing -- Investigating human-robot trust in emergency scenarios: methodological lessons learned -- Designing for robust and effective teamwork in human-agent teams -- Measuring Trust in Human Robot Interactions: Development of the zTrust Perception Scale-HRIy -- Methods for developing trust models for intelligent systems -- The intersection of robust intelligence and trust: Hybrid teams, firms & systems.
520 3 _aThis volume explores the intersection of robust intelligence (RI) and trust in autonomous systems across multiple contexts among autonomous hybrid systems, where hybrids are arbitrary combinations of humans, machines and robots. To better understand the relationships between artificial intelligence (AI) and RI in a way that promotes trust between autonomous systems and human users, this book explores the underlying theory, mathematics, computational models, and field applications. It uniquely unifies the fields of RI and trust and frames it in a broader context, namely the effective integration of human-autonomous systems. A description of the current state of the art in RI and trust introduces the research work in this area. With this foundation, the chapters further elaborate on key research areas and gaps that are at the heart of effective human-systems integration, including workload management, human computer interfaces, team integration and performance, advanced analytics, behavior modeling, training, and, lastly, test and evaluation. Written by international leading researchers from across the field of autonomous systems research, Robust Intelligence and Trust in Autonomous Systems dedicates itself to thoroughly examining the challenges and trends of systems that exhibit RI, the fundamental implications of RI in developing trusted relationships with present and future autonomous systems, and the effective human systems integration that must result for trust to be sustained. Contributing authors: David W. Aha, Jenny Burke, Joseph Coyne, M.L. Cummings, Munjal Desai, Michael Drinkwater, Jill L. Drury, Michael W. Floyd, Fei Gao, Vladimir Gontar, Ayanna M. Howard, Mo Jamshidi, W.F. Lawless, Kapil Madathil, Ranjeev Mittu, Arezou Moussavi, Gari Palmer, Paul Robinette, Behzad Sadrfaridpour, Hamed Saeidi, Kristin E. Schaefer, Anne Selwyn, Ciara Sibley, Donald A. Sofge, Erin Solovey, Aaron Steinfeld, Barney Tannahill, Gavin Taylor, Alan R. Wagner, Yue Wang, Holly A. Yanco, Dan Zwillinger.
988 0 0 _aEBOOK, EBSPRINGER
650 7 _aInteligencia artificial
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_0comprobar BNE19900997218
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700 1 _aMittu, Ranjeev.
_eeditor literario
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700 1 _aSofge, Donald.
_eeditor literario
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700 1 _aWagner, Alan.
_eeditor literario
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700 1 _aLawless, W. F.
_eeditor literario
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856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-1-4899-7668-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9781489976680
907 _a.b12936935
_b10-10-17
_c21-11-16
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945 _aQ335 .R638 2016 EB
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