TY - JOUR
T1 - On discrete preferences and coordination
AU - Chierichetti, Flavio
AU - Kleinberg, Jon
AU - Oren, Sigal
N1 - Funding Information:
This work has been supported in part by a Simons Investigator Award , a Google Research Grant, an ARO MURI grant, and NSF grants IIS-0910664 , CCF-0910940 , IIS-1016099 and a Microsoft Research Fellowship.
Publisher Copyright:
© 2017 Elsevier Inc.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - An active line of research has considered games played on networks in which payoffs depend on both a player's individual decision and the decisions of her neighbors. A basic question that has remained largely open is to consider games where the players’ strategies come from a fixed, discrete set, and where players may have different preferences among the possible strategies. We develop a set of techniques for analyzing this class of games, which we refer to as discrete preference games. We parametrize the games by the relative extent to which a player takes into account the effect of her preferred strategy and the effect of her neighbors’ strategies, allowing us to interpolate between network coordination games and unilateral decision-making. We focus on the efficiency of the best Nash equilibrium and provide conditions on when the optimal solution is also a Nash equilibrium.
AB - An active line of research has considered games played on networks in which payoffs depend on both a player's individual decision and the decisions of her neighbors. A basic question that has remained largely open is to consider games where the players’ strategies come from a fixed, discrete set, and where players may have different preferences among the possible strategies. We develop a set of techniques for analyzing this class of games, which we refer to as discrete preference games. We parametrize the games by the relative extent to which a player takes into account the effect of her preferred strategy and the effect of her neighbors’ strategies, allowing us to interpolate between network coordination games and unilateral decision-making. We focus on the efficiency of the best Nash equilibrium and provide conditions on when the optimal solution is also a Nash equilibrium.
KW - Algorithmic game theory
KW - Price of stability
UR - http://www.scopus.com/inward/record.url?scp=85036625686&partnerID=8YFLogxK
U2 - 10.1016/j.jcss.2017.11.002
DO - 10.1016/j.jcss.2017.11.002
M3 - Article
AN - SCOPUS:85036625686
SN - 0022-0000
VL - 93
SP - 11
EP - 29
JO - Journal of Computer and System Sciences
JF - Journal of Computer and System Sciences
ER -