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arXiv · 0705.4025

Stochastic analysis of an agent-based model

A. Veglio·M. Marsili
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Abstract

We analyze the dynamics of a forecasting game which exhibits the phenomenon of information cascades. Each agent aims at correctly predicting a binary variable and he/she can either look for independent information or herd on the choice of others. We show that dynamics can be analitically described in terms of a Langevin equation and its collective behavior is described by the solution of a Kramers' problem. This provides very accurate results in the region where the vast majority of agents herd, which corresponds to the most interesting one from a game theoretic point of view.

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BibTeXRIS

A. Veglio, M. Marsili. 2007-05-28. Stochastic analysis of an agent-based model. https://doi.org/10.1016/j.physa.2007.07.027

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