This paper studies the evolutionary prisoner's dilemma game (PDG) in finite dynamic scale-free networks, where
the dynamic property is fulfilled by considering an epidemic process in networks. When a person is in infected
state, he will not play PDG. Only healthy persons play PDG with their healthy neighbors. Our simulations show
that (i) the ratio of healthy persons, R<sub>s</sub>, depends not only on the spreading rate λ, but also on the recovery
rate δ; (ii) The relationship between cooperation behaviors and the spreading rate λ depends on the value of δ;
(iii) Given the same value of R<sub>s</sub> and payoff parameter <i>b</i>, the cooperation frequency <i>f</i> changes with δ; (iv) Some
curves of <i>f</i> against R<sub>s</sub> are monotonic while others are non-monotonic. We have qualitatively explained results
(ii)-(iv) through competition mechanism of cooperation enhancement effect and cooperation suppression effect.
Our work sheds some lights on the important effect of dynamic topology on evolutionary game.
In this paper, we study the Prisoner's Dilemma Game (PDG) on a scale-free social network where the agents participate the game with a probability proportional to the power of their degree, i.e., P<sub>i</sub> ~ k<sup>α</sup><sub>i</sub>. In this way, the agents' participation in the game change with time, and our study reveals some properties of PDG in a dynamic social structure. In the generations each active player updates its strategy by following one of the active neighbors' strategy with a probability dependent on the payoff difference. Simulation shows the dynamic
attending of agents has an important effect on the evolutionary game. In order to enhance cooperation behavior,
we need to constrain participant of low-degree agents and encourage participant of high-degree agents in the
game. In most cases, a maximum cooperation frequency is achieved when α is set to be slightly higher than
zero. Our study may also shed some light on the policy construction of government.