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Modeling Decisions for Artificial Intelligence : 17th International Conference, MDAI 2020, Sant Cugat, Spain, September 2-4, 2020, Proceedings / edited by Vicenç Torra, Yasuo Narukawa, Jordi Nin, Núria Agell.
SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online
View online- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 12256
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 12256
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer networks.
- Computer science-Mathematics.
- Computer science.
- Application software.
- Artificial Intelligence.
- Computer Communication Networks.
- Mathematics of Computing.
- Theory of Computation.
- Computer and Information Systems Applications.
- Local Subjects:
- Artificial Intelligence.
- Computer Communication Networks.
- Mathematics of Computing.
- Theory of Computation.
- Computer and Information Systems Applications.
- Physical Description:
- 1 online resource (XIII, 299 pages) : 91 illustrations, 42 illustrations in color.
- Edition:
- 1st edition 2020.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2020.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.* The 24 papers presented in this volume were carefully reviewed and selected from 46 submissions. They discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making, and data science and data mining. * The conference was canceled due to the COVID-19 pandemic.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-57524-3
- 9783030575243
- Access Restriction:
- Restricted for use by site license.
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