Too many options to choice and often contradictive selecting criteria 
are two major problems remaining in intelligent decision makings.The 
first problem may be solved with rough set, especially Probabilistic 
rough sets to form three-way or ternary decision-making. The second 
problem may be solved by game theory which balances multiple 
contradictive decision criteria for rational decision making. 
Probabilistic rough sets aim to lose the often too strict conditions 
in the traditional Pawlak rough sets by introducing a pair of 
thresholds $(\alpha,\beta)$ for lower and upper approximations 
regions. The game-theoretic rough set (GTRS) model determines the 
optimal thresholds by setting up a game for trading-off between 
different criteria. The GTRS model meets the challenge for determining 
a balanced and optimal threshold pair that leads to a moderate, cost 
effective or efficient level of acceptance, rejection or deferment 
decision by providing a game mechanism. We will review basic concepts 
of theoretic rough set model and its recent development in this talk.