Bhattacherjee Biplab, Manna S S, Mukherjee Animesh
Satyendra Nath Bose National Centre for Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata 700098, India.
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Jun;87(6):062808. doi: 10.1103/PhysRevE.87.062808. Epub 2013 Jun 17.
We present the results of a detailed numerical study of a model for the sharing and sorting of information in a community consisting of a large number of agents. The information gathering takes place in a sequence of mutual bipartite interactions where randomly selected pairs of agents communicate with each other to enhance their knowledge and sort out the common information. Although our model is less restricted compared to the well-established naming game, the numerical results strongly indicate that the whole set of exponents characterizing this model are different from those of the naming game and they assume nontrivial values. Finally, it appears that in analogy to the emergence of clusters in the phenomenon of percolation, one can define clusters of agents here having the same information. We have studied in detail the growth of the largest cluster in this article and performed its finite-size scaling analysis.
我们展示了对一个由大量智能体组成的社区中信息共享与分类模型的详细数值研究结果。信息收集通过一系列相互的双边交互进行，其中随机选择的智能体对相互交流以增进彼此知识并梳理出共同信息。尽管我们的模型与成熟的命名博弈相比限制较少，但数值结果强烈表明，表征该模型的整套指数与命名博弈的指数不同，且它们取非平凡值。最后，类似于渗流现象中簇的出现，似乎在此可以定义具有相同信息的智能体簇。在本文中，我们详细研究了最大簇的增长，并对其进行了有限尺寸标度分析。
