▁info - g ap ' s ▁models ▁are ▁mathematical . ▁ ▁Gener ic ▁models ▁▁ ▁The ▁basic ▁concept ual ▁framework ▁that ▁classical ▁decision ▁theory ▁provides ▁for ▁dealing ▁with ▁uncertainty ▁is ▁that ▁of ▁a ▁two - player ▁game . ▁ ▁The ▁two ▁players ▁are ▁the ▁decision ▁mak er ▁( DM ) ▁and ▁Nature , ▁where ▁Nature ▁represents ▁uncertainty . ▁More ▁specifically , ▁Nature ▁represents ▁the ▁DM ' s ▁attitude ▁towards ▁uncertainty ▁and ▁risk . ▁ ▁Note ▁that ▁a ▁clear ▁distinction ▁is ▁made ▁in ▁this ▁regard ▁between ▁a ▁p ess im istic ▁decision ▁mak er ▁and ▁an ▁optim istic ▁decision ▁mak er , ▁ ▁namely ▁between ▁a ▁worst - case ▁attitude ▁and ▁a ▁best - case ▁attitude . ▁A ▁p ess im istic ▁decision ▁mak er ▁assumes ▁that ▁Nature ▁plays ▁against ▁him ▁whereas ▁an ▁optim istic ▁decision ▁mak er ▁assumes ▁that ▁Nature ▁plays ▁with ▁him . ▁ ▁To ▁express ▁these ▁intuit ive ▁not ions ▁mathemat ically , ▁classical ▁decision ▁theory ▁uses ▁a ▁simple ▁model ▁consisting ▁of ▁the ▁following ▁three ▁construct s : ▁▁ ▁A ▁set ▁ ▁representing ▁the ▁decision ▁space ▁available ▁to ▁the ▁DM . ▁ ▁A ▁set ▁of ▁sets ▁ ▁representing ▁state ▁spaces ▁associated ▁with ▁the ▁dec isions ▁in ▁ ▁. ▁ ▁A ▁function ▁ ▁st ip ulating ▁the ▁out comes ▁generated ▁by ▁the ▁ ▁decision - state ▁pairs ▁. ▁ ▁The ▁function ▁ ▁is ▁called ▁objective ▁function , ▁pay off ▁function , ▁return ▁function , ▁cost ▁function ▁ ▁etc . ▁ ▁The ▁decision - making ▁process ▁( game ) ▁defined ▁by ▁these ▁objects