NDLI: Revisiting log-linear learning: Asynchrony, completeness and payoff-based implementation

Content Provider	IEEE Xplore Digital Library
Author	Marden, J.R. Shamma, J.S.
Copyright Year	2010
Description	Author affiliation: School of Electrical and Computer Engineering, Georgia Institute of Technology, 777 Atlantic Dr NW, Atlanta, 30332-0250, USA (Shamma, J.S.) \|\| Department of Electrical, Computer, and Energy Engineering, University of Colorado at Boulder, 425 UBC, 80309, USA (Marden, J.R.)
Abstract	The theory of learning in games has sought to understand how and why equilibria emerge in non-cooperative games. Traditionally, social science literature develops descriptive game theoretic models for players, analyzes the limiting behavior, and generalizes the results for larger classes of games. Recently, there has been a significant amount of research seeking to understand these behavioral models not from a descriptive point of view, but rather from a prescriptive point of view [1]–[4]. The goal is to use these behavioral models as a prescriptive control approach in distributed multi-agent systems where the guaranteed limiting behavior would represent a desirable operating condition.
Starting Page	1171
Ending Page	1172
File Size	294194
Page Count	2
File Format	PDF
ISBN	9781424482153
e-ISBN	9781424482160
DOI	10.1109/ALLERTON.2010.5707044
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics Multiagent systems Limiting Noise Games Nash equilibrium Joints
Content Type	Text
Resource Type	Article

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