Signal Processing - January 2016 - 94
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Game Theory
for Networks
[A tutorial on game-theoretic tools for emerging
signal processing applications]
[Giacomo Bacci, Samson Lasaulce, Walid Saad, and Luca Sanguinetti]
T
he aim of this tutorial is to provide an overview,
although necessarily incomplete, of game theory (GT)
for signal processing (SP) in networks. One of the
main features of this contribution is to gather in a single article some fundamental game-theoretic notions
and tools that, over the past few years, have become widespread in
the SP literature. In particular, both strategic-form and coalitionform games are described in detail, and the key connections and
differences between them are outlined. Moreover, particular attention is also devoted to clarifying the connections between strategic-form games and distributed optimization and learning
algorithms. Beyond an introduction to the basic concepts and
Digital Object Identifier 10.1109/MSP.2015.2451994
Date of publication: 29 December 2015
main solution approaches, several carefully designed examples are
provided to allow a better understanding of how to apply the
described tools.
InTroducTIon
GT is a branch of mathematics that enables the modeling and
analysis of the interactions between several decision makers
(called players) who can have conflicting or common objectives. A
game is a situation in which the benefit or cost achieved by each
player from an interactive situation depends not only on its own
decisions but also on those taken by the other players. For example, the time a car driver needs to get home generally depends not
only on the route he or she chooses but also on the decisions
made by the other drivers. Therefore, in a game, the actions and
objectives of the players are tightly coupled. Until very recently, GT
IEEE SIGNAL PROCESSING MAGAZINE [94] JANuARy 2016
1053-5888/16©2016IEEE
Table of Contents for the Digital Edition of Signal Processing - January 2016
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