Strategy optimization of weighted networked evolutionary games with switched topologies and threshold

摘要

In real life, whether individuals or enterprises there have a lot of objects which are related to them, but they will choose the objects they trust to refer to their information and play games with them. In this study, a model is established named the weighted networked evolutionary games(NEGs) with switched topologies, which describes that each player can choose the networks he is eager to attend at different moments, and in the selected network each player will choose the real neighborhood players called trusters, according to his own criteria. Using the semi-tensor product(STP) of matrices, the algebraic representation of the new model’s evolution process is obtained. It is known that players have a minimum payoff threshold to survive, so the strategy optimization algorithm is designed through the method of state feedback control so that players’ strategy choices can reach the threshold as they evolve. An example is given to illustrate the effectiveness of algorithms.