Network reciprocity by coexisting learning and teaching strategies
Network reciprocity by coexisting learning and teaching strategies
复制标题
DOI：
10.1103/physreve.85.032101
复制
发表时间：
2012-03-21
影响因子：
2.4
通讯作者：
Yamauchi, Atsuo
中科院分区：
文献类型：
--
作者：
Tanimoto, Jun;Brede, Markus;Yamauchi, Atsuo
我们提出了一个网络互惠模型，在该模型中，代理概率地采取学习或教学策略。在学习适应机制中，智能体可以通过费米两两比较来复制邻居的策略。教学适应机制涉及代理将其策略强加给邻居。我们的模拟表明，学习和教学代理在网络中共存的频率和网络结构本身都对互惠有显著影响。
We propose a network reciprocity model in which an agent probabilistically adopts learning or teaching strategies. In the learning adaptation mechanism, an agent may copy a neighbor's strategy through Fermi pairwise comparison. The teaching adaptation mechanism involves an agent imposing its strategy on a neighbor. Our simulations reveal that the reciprocity is significantly affected by the frequency with which learning and teaching agents coexist in a network and by the structure of the network itself.