Journal article
LEARNING IN BAYESIAN GAMES BY BOUNDED RATIONAL PLAYERS I
Macroeconomic dynamics, Vol.1(3), pp.568-587
1997
DOI: 10.1017/S1365100597004021
Abstract
We study learning in Bayesian games (or games with differential
information) with an arbitrary number of bounded rational players,
i.e., players who choose approximate best response strategies
[approximate Bayesian Nash Equilibrium (BNE) strategies] and who also
are allowed to be completely irrational in some states of the world.
We show that bounded rational players by repetition can reach a limit
full information BNE outcome. We also prove the converse, i.e., given
a limit full information BNE outcome, we can construct a sequence of
bounded rational plays that converges to the limit full information
BNE outcome.
Details
- Title: Subtitle
- LEARNING IN BAYESIAN GAMES BY BOUNDED RATIONAL PLAYERS I
- Creators
- TAESUNG Kim - Seoul National UniversityNICHOLAS C. Yannelis - University of Illinois Urbana-Champaign
- Resource Type
- Journal article
- Publication Details
- Macroeconomic dynamics, Vol.1(3), pp.568-587
- Publisher
- Cambridge University Press
- DOI
- 10.1017/S1365100597004021
- ISSN
- 1365-1005
- eISSN
- 1469-8056
- Number of pages
- 20
- Language
- English
- Date published
- 1997
- Academic Unit
- Economics
- Record Identifier
- 9984380544202771
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