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Reciprocity, evolution, and decision games in network and data science / Yan Chen, University of Science and Technology of China, Chih-Yu Wang, Academia Sinica, Chunxiao Jiang, Tsinghua University, K.J. Ray Liu, University of Maryland, College Park.

By: Contributor(s): Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2021Description: 1 online resource (xv, 457 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781108859783 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 003/.72 23
LOC classification:
  • T57.92 .C44 2021
Online resources: Summary: Learn how to analyse and manage evolutionary and sequential user behaviours in modern networks, and how to optimize network performance by using indirect reciprocity, evolutionary games, and sequential decision making. Understand the latest theory without the need to go through the details of traditional game theory. With practical management tools to regulate user behaviour, and simulations and experiments with real data sets, this is an ideal tool for graduate students and researchers working in networking, communications, and signal processing.
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Item type Current library Collection Call number Status Date due Barcode
eBooks eBooks Central Library Computer Science Available EB0919

Title from publisher's bibliographic system (viewed on 09 Jul 2021).

Learn how to analyse and manage evolutionary and sequential user behaviours in modern networks, and how to optimize network performance by using indirect reciprocity, evolutionary games, and sequential decision making. Understand the latest theory without the need to go through the details of traditional game theory. With practical management tools to regulate user behaviour, and simulations and experiments with real data sets, this is an ideal tool for graduate students and researchers working in networking, communications, and signal processing.

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