Predicting Human Decision-Making: From Prediction to Action, Ariel Rosenfeld, Sarit Kraus
Автор: Ariel Rosenfeld, Sarit Kraus Название: Predicting Human Decision-Making: From Prediction to Action ISBN: 1681732769 ISBN-13(EAN): 9781681732763 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 87780.00 T Наличие на складе: Невозможна поставка. Описание: Human decision-making often transcends our formal models of ""rationality."" Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.
Название: Predicting structured data ISBN: 0262528045 ISBN-13(EAN): 9780262528047 Издательство: MIT Press Рейтинг: Цена: 57030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.
Contributors Yasemin Altun, Gokhan Bakir, Olivier Bousquet, Sumit Chopra, Corinna Cortes, Hal Daume III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, Thomas Hofmann, Fu Jie Huang, Yann LeCun, Tobias Mann, Daniel Marcu, David McAllester, Mehryar Mohri, William Stafford Noble, Fernando Perez-Cruz, Massimiliano Pontil, Marc'Aurelio Ranzato, Juho Rousu, Craig Saunders, Bernhard Scholkopf, Matthias W. Seeger, Shai Shalev-Shwartz, John Shawe-Taylor, Yoram Singer, Alexander J. Smola, Sandor Szedmak, Ben Taskar, Ioannis Tsochantaridis, S.V.N Vishwanathan, Jason Weston
Автор: Dylan D. Schmorrow; Cali M. Fidopiastis Название: Foundations of Augmented Cognition. Advancing Human Performance and Decision-Making through Adaptive Systems ISBN: 3319075268 ISBN-13(EAN): 9783319075266 Издательство: Springer Рейтинг: Цена: 68010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 8th International Conference on the Foundations of Augmented Cognition, AC 2014, held as part of HCI International 2014 which took place in Heraklion, Crete, Greece, in June 2014 and incorporated 14 conferences which similar thematic areas.
The two-volume set LNCS 10273 and 10274 constitutes the refereed proceedings of the thematic track on Human Interface and the Management of Information, held as part of the 19th HCI International 2017, in Vancouver, BC, Canada, in July 2017.
HCII 2017 received a total of 4340 submissions, of which 1228 papers were accepted for publication after a careful reviewing process. The 102 papers presented in these volumes were organized in topical sections as follows: Part I: Visualization Methods and Tools; Information and Interaction Design; Knowledge and Service Management; Multimodal and Embodied Interaction. Part II: Information and Learning; Information in Virtual and Augmented Reality; Recommender and Decision Support Systems; Intelligent Systems; Supporting Collaboration and User Communities; Case Studies.
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