Networks and learning in game theory

W. Kets

Research output: ThesisDoctoral ThesisScientific

409 Downloads (Pure)

Abstract

This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network. Players only have incomplete information on the network structure. The first part of this thesis studies how players' beliefs over the network they belong to affect game-theoretic outcomes, and develops a natural model for players' beliefs. The second part of this thesis focuses on learning in games. An intuitive learning model is introduced, and the predictions of this model are analyzed. Furthermore, learning in a class of congestion games is studied from different perspectives.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Tilburg University
Supervisors/Advisors
  • Talman, A.J.J., Promotor
  • Goyal, S., Promotor, External person
  • Voorneveld, M., Co-promotor
Award date9 Apr 2008
Place of PublicationTilburg
Publisher
Print ISBNs97890568211
Publication statusPublished - 2008

Fingerprint

Game theory
Circuit theory

Cite this

Kets, W. (2008). Networks and learning in game theory. Tilburg: CentER, Center for Economic Research.
Kets, W.. / Networks and learning in game theory. Tilburg : CentER, Center for Economic Research, 2008. 295 p.
@phdthesis{7713fce13131498c8c6f39c4ab38c4bd,
title = "Networks and learning in game theory",
abstract = "This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network. Players only have incomplete information on the network structure. The first part of this thesis studies how players' beliefs over the network they belong to affect game-theoretic outcomes, and develops a natural model for players' beliefs. The second part of this thesis focuses on learning in games. An intuitive learning model is introduced, and the predictions of this model are analyzed. Furthermore, learning in a class of congestion games is studied from different perspectives.",
author = "W. Kets",
year = "2008",
language = "English",
isbn = "97890568211",
series = "CentER Dissertation Series",
publisher = "CentER, Center for Economic Research",
school = "Tilburg University",

}

Kets, W 2008, 'Networks and learning in game theory', Doctor of Philosophy, Tilburg University, Tilburg.

Networks and learning in game theory. / Kets, W.

Tilburg : CentER, Center for Economic Research, 2008. 295 p.

Research output: ThesisDoctoral ThesisScientific

TY - THES

T1 - Networks and learning in game theory

AU - Kets, W.

PY - 2008

Y1 - 2008

N2 - This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network. Players only have incomplete information on the network structure. The first part of this thesis studies how players' beliefs over the network they belong to affect game-theoretic outcomes, and develops a natural model for players' beliefs. The second part of this thesis focuses on learning in games. An intuitive learning model is introduced, and the predictions of this model are analyzed. Furthermore, learning in a class of congestion games is studied from different perspectives.

AB - This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network. Players only have incomplete information on the network structure. The first part of this thesis studies how players' beliefs over the network they belong to affect game-theoretic outcomes, and develops a natural model for players' beliefs. The second part of this thesis focuses on learning in games. An intuitive learning model is introduced, and the predictions of this model are analyzed. Furthermore, learning in a class of congestion games is studied from different perspectives.

M3 - Doctoral Thesis

SN - 97890568211

T3 - CentER Dissertation Series

PB - CentER, Center for Economic Research

CY - Tilburg

ER -

Kets W. Networks and learning in game theory. Tilburg: CentER, Center for Economic Research, 2008. 295 p. (CentER Dissertation Series).