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Quantum-Like Models for Information Retrieval and Decision-Making - 2019 ed.

By: (Edited by) Andrei Khrennikov , (Edited by) Bourama Toni , (Edited by) Diederik Aerts , (Edited by) Massimo Melucci

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Ksh 21,600.00

Format: Paperback / Softback

ISBN-10: 3030259153

ISBN-13: 9783030259150

Edition: 2019 ed.

Series: STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 20th, 2020

Print length: 173 Pages

Product Classification: Mathematical physics

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Recent years have been characterized by tremendous advances in quantum information and communication, both theoretically and experimentally.
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 considered chiefly 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; and theory of contextual probability. 

The book offers young scientists (students, PhD, postdocs) an essential introduction to applying the mathematical apparatus of quantum theory to computer science, information retrieval, and information processes. 


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