Convergence results on stochastic adaptive learning

Naoki Funai ()
Additional contact information
Naoki Funai: Ryutsu Keizai University

Economic Theory, 2019, vol. 68, issue 4, No 6, 907-934

Abstract: Abstract We investigate an adaptive learning model which nests several existing learning models such as payoff assessment learning, valuation learning, stochastic fictitious play learning, experience-weighted attraction learning and delta learning with foregone payoff information in normal form games. In particular, we consider adaptive players each of whom assigns payoff assessments to his own actions, chooses the action which has the highest assessment with some perturbations and updates the assessments using observed payoffs, which may include payoffs from unchosen actions. Then, we provide conditions under which the learning process converges to a quantal response equilibrium in normal form games.

Keywords: Adaptive learning; Normal form games; Asynchronous stochastic approximation; Quantal response equilibrium (search for similar items in EconPapers)
JEL-codes: C72 D83 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s00199-018-1150-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joecth:v:68:y:2019:i:4:d:10.1007_s00199-018-1150-8

Ordering information: This journal article can be ordered from
http://www.springer. ... eory/journal/199/PS2

DOI: 10.1007/s00199-018-1150-8

Access Statistics for this article

Economic Theory is currently edited by Nichoals Yanneils

More articles in Economic Theory from Springer, Society for the Advancement of Economic Theory (SAET) Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().