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In this study, we propose a spatial prisoner's dilemma game model with a 2-stage strategy updating rule, and focus on the cooperation behavior of the system. In the first stage, i.e., the pre-learning stage, a focal player decides whether to update his strategy according to the pre-learning factor β and the payoff difference between himself and the average of his neighbors. If the player makes up his mind to update, he enters into the second stage, i.e., the learning stage, and adopts a strategy of a randomly selected neighbor according to the standard Fermi updating rule. The simulation results show that the cooperation level has a non-trivial dependence osn the pre-learning factor. Generally, the cooperation frequency decreases as the pre-learning factor increases; but a high cooperation level can be obtained in the intermediate region of -3 < β < -1. We then give some explanations via studying the co-action of pre-learning and learning. Our results may sharpen the understanding of the influence of the strategy updating rule on evolutionary games. [ABSTRACT FROM AUTHOR]

In this paper, an analogue model of a memristor using a light-dependent resistor (LDR) is presented. This model can be simplified into two parts: a control circuit and a variable resistor. It can be used to easily verify theoretical presumptions about the switching properties of memristors. This LDR-based memristor model can also be used in both simulations and experiments for future research into memristor applications. The paper includes mathematical models, simulations, and experimental results. [ABSTRACT FROM AUTHOR]