Arbeitspapier
Learning in Networks Contexts: Experimental Results from Simulations
This paper describes the results of simulation experiments performed on a suite of learning algorithms. We focus on games in {\em network contexts}. These are contexts in which (1) agents have very limited information about the game; users do not know their own (or any other agent's) payoff function, they merely observe the outcome of their play. (2) Play can be extremely asynchronous; players update their strategies at very different rates. There are many proposed learning algorithms in the literature. We choose a small sampling of such algorithms and use numerical simulation to explore the nature of asymptotic play. In particular, we explore the extent to which the asymptotic play depends on three factors, namely: limited information, asynchronous play, and the degree of responsiveness of the learning algorithm.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 1998-25
- Klassifikation
-
Wirtschaft
Noncooperative Games
- Thema
-
learning
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Friedman, Eric
Shenker, Scott
Greenwald, Amy
- Ereignis
-
Veröffentlichung
- (wer)
-
Rutgers University, Department of Economics
- (wo)
-
New Brunswick, NJ
- (wann)
-
1998
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Friedman, Eric
- Shenker, Scott
- Greenwald, Amy
- Rutgers University, Department of Economics
Entstanden
- 1998
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