@booklet {zamir-iigatnd1995,
	title = {Incomplete Information Games and the Normal Distribution},
	howpublished = {Discussion Papers},
	year = {1995},
	month = {2},
	abstract = {We consider a repeated two-person zero-sum game in which the payoffs in the stage game are given by a 2 \% 2 matrix. This is chosen (once) by chance, at the beginning of the game, to be either G1 or G{\texttwosuperior}, with probabilities p and 1 - p respectively. The maximizer is informed of the actual payoff matrix chosen but the minimizer is not. Denote by vn(p) the value of the n -times repeated game (with the payoff function defined as the average payoff per stage), and by v\%(p) the value of the infinitely repeated game. It is proved that vn(p)=v\%(p) + \%(p)\%(p)/\%n + \%\%1/\%n\% , where \%(p) is on appropriately scaled normal distributiondensity function evaluated at its p-quantile, and the coefficient K(p) is either 0 or the absolute value of a linear function in p.},
	url = {/files/dp70.pdf},
	author = {Zamir, Jean-Francois Mertens and Shmuel}
}
