Traulsen Arne, Röhl Torsten, Schuster Heinz Georg
Institut für Theoretische Physik und Astrophysik, Christian-Albrechts Universität, Olshausenstrasse 40, 24098 Kiel, Germany.
Phys Rev Lett. 2004 Jul 9;93(2):028701. doi: 10.1103/PhysRevLett.93.028701.
We introduce an extension of the usual replicator dynamics to adaptive learning rates. We show that a population with a dynamic learning rate can gain an increased average payoff in transient phases and can also exploit external noise, leading the system away from the Nash equilibrium, in a resonancelike fashion. The payoff versus noise curve resembles the signal to noise ratio curve in stochastic resonance. Seen in this broad context, we introduce another mechanism that exploits fluctuations in order to improve properties of the system. Such a mechanism could be of particular interest in economic systems.
我们将通常的复制者动态扩展到自适应学习率。我们表明,具有动态学习率的群体在过渡阶段可以获得更高的平均收益,并且还可以利用外部噪声,以类似共振的方式使系统偏离纳什均衡。收益与噪声曲线类似于随机共振中的信噪比曲线。从这个广义的背景来看,我们引入了另一种利用波动来改善系统性能的机制。这种机制在经济系统中可能特别有意义。