  The evolutionary Prisoner's Dilemma Game (PDG) and the Snowdrift Game (SG)
with preferential learning mechanism are studied in the Barab\'asi-Albert
network. Simulation results demonstrate that the preferential learning of
individuals remarkably promotes the cooperative behavior for both two games
over a wide range of payoffs. To understand the effect of preferential learning
on the evolution of the systems, we investigate the time series of the
cooperator density for different preferential strength and payoffs. It is found
that in some specific cases two games both show the $1/f$-scaling behaviors,
which indicate the existence of long range correlation. We also figure out that
when the large degree nodes have high probability to be selected, the PDG
displays a punctuated equilibrium-type behavior. On the contrary, the SG
exhibits a sudden increase feature. These temporary instable behaviors are
ascribed to the strategy shift of the large degree nodes.
