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SFB 504 discussion paper No. 98-46:

Simultaneous evolution of learning rules and strategies

Oliver Kirchkamp


We study a model of local evolution in which agents located on a network interact strategically with their neighbours. Strategies are chosen with the help of learning rules that are themselves based on the success of strategies observed in the neighbourhood.

Previous work on local evolution assumes fixed learning rules while we study learning rules that are determined endogenously.

Simulations indicate that endogenous learning rules put more weight on a learning player's own experience than on the experience of an observed neighbour. Nevertheless stage game behaviour is similar to behaviour with symmetric learning rules.

Keywords: Evolutionary Game Theory, Learning, Local Interaction, Networks.

JEL-Code: C63, C72, D62, D63, D73, D83, R12,R13.

Click here for a copy of the SFB 504 - paper as a PDF file (400 kB, 27 pages).
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Meanwhile the paper has been published as
Financial support from the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 303 at the University of Bonn is gratefully acknowledged. I thank Georg Nöldeke, Karl Schlag and Avner Shaked for comments.