一个基于Agent模型的随机分析
Stochastic analysis of an agent-based model
摘要：
我们分析了一个预测游戏，表现出的信息级联现象的动态。每个代理的目标是正确预测一个二元变量，他/她可以寻找独立的信息或羊群的选择。我们表明，动力学可以分析描述的朗之万方程和它的集体行为描述的Kramers问题的解决方案。这提供了非常准确的结果，在该地区的绝大多数代理羊群，这对应于最有趣的一个从博弈论的角度来看。
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
