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Paperback. Zustand: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Used book that is in clean, average condition without any missing pages.

Soft cover. Zustand: Fair. No Jacket. First Edition. Clean And Unmarked 1980 Copyright In Soft Cover Format, Word Problems Practice Book, First Edition: Guided Practice Workbook With Introduction, Whole Numbers, Fractions, Money, Percentages, Time, Graphs, Map, Charts, Color Illustrations, 126 Pages, Pink And Black Cover, Issued Without Answers, 0883099195 (1980 Copyright) D3.

Zustand: Good. Used book that is in clean, average condition without any missing pages.

Paperback. Zustand: Fair. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Zustand: Good. Good condition. (juvenile, non-fiction, addition, math) A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

XII, 270 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Zustand: New.

Paperback. Zustand: Brand New. 1st edition. 315 pages. 9.00x6.00x0.50 inches. In Stock.

hardcover. Zustand: Very Good.

Zustand: New.

Paperback. Zustand: Brand New. 328 pages. 9.25x6.14x0.94 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Third International Symposium on Quantum Interaction, QI 2009, held in Saarbrücken, Germany, in March 2009. The 21 revised full papers presented together with the 3 position papers were carefully reviewed and selected from numerous submissions. The papers show the cross-disciplinary nature of quantum interaction covering topics such as computation, cognition, decision theory, information retrieval, information systems, social interaction, computational linguistics and finance.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 284 | Sprache: Englisch | Produktart: Bücher | This 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.

Zustand: New. pp. 303.

Kartoniert / Broschiert. Zustand: New.

Taschenbuch. Zustand: Neu. Neuware -Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such asSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 296 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Many current AI and machine learning algorithms and data and information fusion processesattempt in software to estimate situations in our complex world of nested feedback loops. Suchalgorithms and processes must gracefully and efficiently adapt to technical challenges such asdata quality induced by these loops, and interdependencies that vary in complexity, space, andtime.To realize effective and efficient designs of computational systems, a Systems Engineeringperspective may provide a framework for identifying the interrelationships and patterns ofchange between components rather than static snapshots. We must study cascadinginterdependencies through this perspective to understand their behavior and to successfullyadopt complex system-of-systems in society.This book derives in part from the presentations given at the AAAI 2021 Spring Symposiumsession on Leveraging Systems Engineering to Realize Synergistic AI / Machine LearningCapabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics insystems engineering; AI, machine learning, and reasoning; data and information fusion;intelligent systems; autonomous systems; interdependence and teamwork; human-computerinteraction; trust; and resilience.

Zustand: New. pp. 300.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 328 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Hardcover. Zustand: Brand New. 282 pages. 9.50x6.50x0.75 inches. In Stock.

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware -This 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch.

Buch. Zustand: Neu. Neuware -This 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch.

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This 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.

Taschenbuch. Zustand: Neu. Artificial Intelligence for the Internet of Everything | William Lawless (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2019 | Academic Press | EAN 9780128176368 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 584 | Sprache: Englisch | Produktart: Bücher | This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams¿where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.