Adaptive Learning and Emergent Coordination in Minority Games

Giulio Bottazzi, Giovanna Devetag, Giovanni Dosi
Authors registered in the RePEc Author Service: Giovanni Dosi, Giovanna Devetag and Giulio Bottazzi

No 20, Computing in Economics and Finance 2001 from Society for Computational Economics

Abstract: The work studies the properties of a coordination game in which agents repeatedly compete to be in the population minority. The game reflects some essential features of those economic situations in which positive rewards are assigned to individuals who behave in opposition to the modal behavior in a population. Here we model a group of heterogeneous agents who adaptively learn and we investigate the transient and long-run aggregate properties of the system in terms of both allocative and informational efficiency. Our results show that, first, the system long-run properties strongly depend on the behavioral learning rules adopted, and, second, adding noise at the individual decision level and hence increasing heterogeneity in the population substantially improve aggregate welfare, although at the expense of a longer adjustment phase. In fact, the system achieves in that way a higher level of efficiency compared to that attainable by perfectly rational and completely informed agents.

Keywords: minority game; coordination; speculation; adaptive learning; market efficiency; emergent properties (search for similar items in EconPapers)
JEL-codes: C6 D8 G1 (search for similar items in EconPapers)
Date: 2001-04-01
References: Add references at CitEc
Citations: View citations in EconPapers (6)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Adaptive Learning and Emergent Coordination in Minority Games (1999)
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:sce:scecf1:20

Access Statistics for this paper

More papers in Computing in Economics and Finance 2001 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().