书目名称 | Quantum-Like Models for Information Retrieval and Decision-Making | 编辑 | Diederik Aerts,Andrei Khrennikov,Bourama Toni | 视频video | | 概述 | Highlights state-of-the-art contributions from leading international experts.Touches on problems in information foraging, interactive quantum information access, deep convolutional neural networks, th | 丛书名称 | STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health | 图书封面 |  | 描述 | Recent years have been characterized by tremendous advances in quantum information and communication, both theoretically and experimentally. In addition, mathematical methods of quantum information and quantum probability have begun spreading to other areas of research, beyond physics. One exciting new possibility involves applying these methods to information science and computer science (without direct relation to the problems of creation of quantum computers). .The aim of this Special Volume is to encourage scientists, especially the new generation (master and PhD students), working in computer science and related mathematical fields to explore novel possibilities based on the mathematical formalisms of quantum information and probability. The contributing authors, who hail from various countries, combine extensive quantum methods expertise with real-world experience in application of these methods to computer science. The problems consideredchiefly concern quantum information-probability based modeling in the following areas: information foraging; interactive quantum information access; deep convolutional neural networks; decision making; quantum dynamics; open quantum systems | 出版日期 | Book 2019 | 关键词 | operator algebra; probability theory; classical probability theory; quantum probability theory; informat | 版次 | 1 | doi | https://doi.org/10.1007/978-3-030-25913-6 | isbn_softcover | 978-3-030-25915-0 | isbn_ebook | 978-3-030-25913-6Series ISSN 2520-193X Series E-ISSN 2520-1948 | issn_series | 2520-193X | copyright | Springer Nature Switzerland AG 2019 |
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