@ARTICLE{17789162_1972,
author = {Harsanyi, John C. and Selten, Reinhard},
keywords = {},
title = {A generalized Nash solution for two-person bargaining games with
incomplete information },
journal = {Management Science},
year = {1972},
month = {},
volume = {18},
number = {5},
pages = {80-106},
url = {http://ecsocman.hse.ru/text/17789162/},
publisher = {},
language = {ru},
abstract = {The paper extends Nash's theory of two-person bargaining games with
fixed threats to bargaining situations with incomplete information.
After defining such bargaining situations, a formal bargaining model
(bargaining game) will be proposed for them. This bargaining game,
regarded as a noncooperative game, will be analyzed in terms of a
certain class of equilibrium points with special stability
properties, to be called "strict" equilibrium points. Finally an
axiomatic theory will be developed in order to select a unique
solution from the set X of payoff vectors corresponding to such
strict equilibrium points (as well as to probability mixtures of the
latter). It will be shown that the solution satisfying the axioms
proposed in this paper is the point where a certain generalized Nash
product is maximized over this set X. [Авторский текст] },
annote = {The paper extends Nash's theory of two-person bargaining games with
fixed threats to bargaining situations with incomplete information.
After defining such bargaining situations, a formal bargaining model
(bargaining game) will be proposed for them. This bargaining game,
regarded as a noncooperative game, will be analyzed in terms of a
certain class of equilibrium points with special stability
properties, to be called "strict" equilibrium points. Finally an
axiomatic theory will be developed in order to select a unique
solution from the set X of payoff vectors corresponding to such
strict equilibrium points (as well as to probability mixtures of the
latter). It will be shown that the solution satisfying the axioms
proposed in this paper is the point where a certain generalized Nash
product is maximized over this set X. [Авторский текст] }
}