摘要翻译：
我们分析了一个具有信息级联现象的预测博弈的动力学。每个agent的目标是正确地预测一个二元变量，他/她可以寻找独立的信息，也可以选择其他的信息。我们证明了动力学可以用朗之万方程来描述，其集体行为可以用Kramers问题的解来描述。这提供了非常准确的结果，在区域中，绝大多数代理群体，这对应于最有趣的一个从博弈论的观点。
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英文标题：
《Stochastic analysis of an agent-based model》
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作者：
A. Veglio and M. Marsili
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最新提交年份：
2007
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
  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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PDF链接：
https://arxiv.org/pdf/0705.4025