Learning in Network Contexts: Experimental Results from Simulation

نویسندگان

  • Amy Greenwald
  • Eric J. Friedman
  • Scott Shenker
چکیده

This paper describes the results of simulation experiments performed on a suite of learning algorithms. We focus on games in network contexts. These are contexts Ž . Ž . in which 1 agents have very limited information about the game and 2 play can be extremely asynchronous. 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: limited information, asynchronous play, and the degree of responsiveness of the learning algorithm. Journal of Economic Literature Classification Numbers: C63, C72. 2001

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تاریخ انتشار 1999