Discrete-time linear-quadratic mean-field-type repeated games: Perfect, incomplete, and imperfect information

被引:11
|
作者
Barreiro-Gomez, Julian [1 ,2 ]
Duncan, Tyrone E. [3 ]
Tembine, Hamidou [1 ,2 ]
机构
[1] New York Univ Abu Dhabi, Div Engn, Learning & Game Theory Lab L&G Lab, Saadiyat Campus,POB 129188, Abu Dhabi, U Arab Emirates
[2] New York Univ Abu Dhabi, Res Ctr Stabil Instabil & Turbulence SITE, Saadiyat Campus,POB 129188, Abu Dhabi, U Arab Emirates
[3] Univ Kansas, Dept Math, Lawrence, KS 66044 USA
基金
美国国家科学基金会;
关键词
Mean-field-type games; Repeated games; Perfect information; Imperfect information; Mean-variance minimization; Stochastic control; Direct method; Semi-explicit solution;
D O I
10.1016/j.automatica.2019.108647
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we study linear-quadratic mean-field-type repeated games with arbitrary number of interacting decision-makers. Different information structures are examined: (i) perfect knowledge of the model, (ii) imperfect knowledge of the model: under perfect state observation. We provide semi-explicit solutions for both non-cooperative and cooperative cases. The state dynamics is given by a stochastic difference equation that includes mean-field terms, i.e., the expected value for both the state and control inputs. In addition, the cost function incorporates, not only the expected value of the states, but also the variance of both system state and control inputs. The effect of the information is quantified using price of anarchy and price of imperfect information. Finally, some numerical examples are presented. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:16
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