Heterogeneous beliefs and local information in stochastic fictitious play

被引:17
|
作者
Fudenberg, Drew [2 ]
Takahashi, Satoru [1 ]
机构
[1] Princeton Univ, Princeton, NJ 08544 USA
[2] Harvard Univ, Cambridge, MA 02138 USA
关键词
MIXED EQUILIBRIA; GAMES; EVOLUTION; APPROXIMATION; TRAPS; CONSISTENCY; ALGORITHMS; DYNAMICS; POINTS; MODELS;
D O I
10.1016/j.geb.2008.11.014
中图分类号
F [经济];
学科分类号
02 ;
摘要
Stochastic fictitious play (SFP) assumes that agents do not try to influence the future play of their current opponents, an assumption that is justified by appeal to a setting with a large population of players who are randomly matched to play the game. However, the dynamics of SFP have only been analyzed in models where all agents in a player role have the same beliefs. We analyze the dynamics of SFP in settings where there is a population of agents who observe only outcomes in their own matches and thus have heterogeneous beliefs. We provide conditions that ensure that the system converges to a state with homogeneous beliefs, and that its asymptotic behavior is the same as with a single representative agent in each player role. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:100 / 120
页数:21
相关论文
共 50 条
  • [21] No-regret dynamics and fictitious play
    Viossat, Yannick
    Zapechelnyuk, Andriy
    JOURNAL OF ECONOMIC THEORY, 2013, 148 (02) : 825 - 842
  • [22] Stochastic equilibria of an asset pricing model with heterogeneous beliefs and random dividends
    Zhu, Mei
    Wang, Duo
    Guo, Maozheng
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2011, 35 (01) : 131 - 147
  • [23] Generalised Fictitious Play for a Continuum of Anonymous Players
    Rabinovich, Zinovi
    Gerding, Enrico
    Polukarov, Maria
    Jennings, Nicholas R.
    21ST INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-09), PROCEEDINGS, 2009, : 245 - 250
  • [24] A Computationally Efficient Implementation of Fictitious Play in a Distributed Setting
    Swenson, Brian
    Kar, Soummya
    Xavier, Joao
    2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, : 1043 - 1047
  • [25] Entropic Fictitious Play for Mean Field Optimization Problem
    Chen, Fan
    Ren, Zhenjie
    Wang, Songbo
    JOURNAL OF MACHINE LEARNING RESEARCH, 2023, 24
  • [26] Fictitious play for cooperative action selection in robot teams
    Smyrnakis, M.
    Veres, S. M.
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2016, 56 : 14 - 29
  • [27] Empirical Centroid Fictitious Play: An Approach for Distributed Learning in Multi-Agent Games
    Swenson, Brian
    Kar, Soummya
    Xavier, Joao
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (15) : 3888 - 3901
  • [28] Heterogeneous diffusion with stochastic resetting
    Sandev, Trifce
    Domazetoski, Viktor
    Kocarev, Ljupco
    Metzler, Ralf
    Chechkin, Aleksei
    JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL, 2022, 55 (07)
  • [29] Smooth Fictitious Play in N x 2 Potential Games
    Swenson, Brian
    Poor, H. Vincent
    CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2019, : 1739 - 1743
  • [30] DISTRIBUTED FICTITIOUS PLAY FOR MULTI-AGENT SYSTEMS WITH UNCERTAINTY
    Eksin, Ceyhun
    Ribeiro, Alejandro
    2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP), 2016, : 495 - 499