Adaptive Learning and Emergent Coordination in Minority Games
AbstractThe 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.
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Bibliographic InfoPaper provided by Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy in its series LEM Papers Series with number 1999/24.
Date of creation: 03 Dec 1999
Date of revision:
minority game; speculation; adaptive learning; market efficiency; emergent properties;
Other versions of this item:
- Giulio Bottazzi, Giovanna Devetag, Giovanni Dosi, 2001. "Adaptive Learning and Emergent Coordination in Minority Games," Computing in Economics and Finance 2001 20, Society for Computational Economics.
- G1 - Financial Economics - - General Financial Markets
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-05-03 (All new papers)
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- Giorgio Fagiolo & Marco Valente, 2004. "Minority Games, Local Interactions, and Endogenous Networks," LEM Papers Series 2004/17, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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