Reciprocity, Evolution, and Decision Games in Network and Data Science

Description

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.

Yan Chen is a Professor at School of Cyberspace Security, University of Science and Technology of China. Chih-Yu Wang is an Associate Research Fellow at the Research Center for Information Technology Innovation, Academia Sinica. Chunxiao Jiang is an associate professor in the School of Information Science and Technology at Tsinghua University. K.J. Ray Liu is Distinguished University Professor at the University of Maryland, College Park. A Highly Cited Researcher, he is a Fellow of the IEEE and the American Association for the Advancement of Science (AAAS), and National Academy of Inventors. He is the 2021 IEEE President Elect. He is a recipient of the IEEE Fourier Award for Signal Processing and the IEEE Leon K. Kirchmayer Graduate Teaching Award, the IEEE Signal Processing Society 2014 Society Award, and the IEEE Signal Processing Society 2009 Technical Achievement Award. He has also co-authored several books, including Wireless AI (Cambridge, 2019).

'This advanced text is a great start for more in-depth explorations into complex system-modeling areas. Recommended.' J. Brzezinski, Choice Connect