TY - JOUR
T1 - Co-Opetitive Linear-Quadratic Mean-Field-Type Games
AU - Barreiro-Gomez, Julian
AU - Duncan, Tyrone E.
AU - Tembine, Hamidou
N1 - Funding Information:
Manuscript received July 3, 2018; revised November 15, 2018 and January 24, 2019; accepted February 19, 2019. Date of publication March 15, 2019; date of current version December 3, 2020. This work was supported in part by the U.S. Air Force Office of Scientific Research under Grant FA9550-17-1-0259 and Grant FA9550-17-1-0073, and in part by the National Science Foundation under Grant DMS 1411412. This paper was recommended by Associate Editor S. E. Shimony. (Corresponding author: Julian Barreiro-Gomez.) J. Barreiro-Gomez and H. Tembine are with the Learning and Game Theory Laboratory, New York University Abu Dhabi, Abu Dhabi, UAE (e-mail: jbarreiro@nyu.edu; tembine@nyu.edu).
Publisher Copyright:
© 2013 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - In this paper, we propose a co-opetitive mean-field-type game (MFTG) approach in which decision makers interact with each other by means of partial cooperation and competition simultaneously. The proposed novel approach allows decision makers' preferences to evolve over time to cooperate with those who contribute to their utilities, and to compete with those who are working against their individual interests. In addition, we consider that each decision maker has a co-opetitive capacity/power. The co-opetitive MFTG involves concepts, such as selfishness, altruism, competition, cooperation, among others; all together within the same strategic interaction. Both co-opetitive MFTGs and evolutionary dynamics describing the evolution of co-opetitive parameters are combined. We design incentives to promote the emergence of co-opetition over selfish behavior.
AB - In this paper, we propose a co-opetitive mean-field-type game (MFTG) approach in which decision makers interact with each other by means of partial cooperation and competition simultaneously. The proposed novel approach allows decision makers' preferences to evolve over time to cooperate with those who contribute to their utilities, and to compete with those who are working against their individual interests. In addition, we consider that each decision maker has a co-opetitive capacity/power. The co-opetitive MFTG involves concepts, such as selfishness, altruism, competition, cooperation, among others; all together within the same strategic interaction. Both co-opetitive MFTGs and evolutionary dynamics describing the evolution of co-opetitive parameters are combined. We design incentives to promote the emergence of co-opetition over selfish behavior.
KW - Co-opetition
KW - direct method
KW - evolutionary dynamics
KW - learning
KW - mean-field-type games (MFTGs)
UR - http://www.scopus.com/inward/record.url?scp=85072572224&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072572224&partnerID=8YFLogxK
U2 - 10.1109/TCYB.2019.2901006
DO - 10.1109/TCYB.2019.2901006
M3 - Article
C2 - 30892263
AN - SCOPUS:85072572224
SN - 2168-2267
VL - 50
SP - 5089
EP - 5098
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 12
M1 - 8667722
ER -