Social roles as an effective learning mechanism

Using the 'Buyer-Seller' game as an idealized form of social interaction ac ross complementary roles, we examine two forms of 'myopic learning', where individuals try to improve their response to their immediately past (social ) environment. In role sampling, individuals examine a (random) sample of r ole equivalents, 'updating' strategy play by evaluating the success of self and sampled others. In opponent sampling, individuals examine a (random) s ample of potential future 'game opponents' from the population employing th e complementary role. Learning through role sampling can always increase or preserve best response play (to the immediate past), given an appropriate learning rule, while opponent sampling never does; it is thus better to ign ore the world of opponents completely, choosing strategies based on observe d outcomes of role equivalents. Under role learning, play either cycles abo ut or spirals away from the Nash equilibrium of the game, with no one actua lly playing Nash in either case. With moderate rates of learning, the cycle is sufficiently distant from the equilibrium that Nash is of little value in predicting actual strategy play; here, the greater the uncertainty of th e social world (e.g. variable game payoffs, preserving the buyer-seller str ucture), the less useful Nash play as a predictor of actual play. Under mod erate, myopic (role) learning, game-theoretic emphasis on equilibrium as a predictor of individual behavior may be misplaced in even simple social sit uations.