Non-Cooperative Outcomes for Stochastic Nash Games: Decision Strategies towards Multi-Attribute Performance Robustness

Abstract

The advantages of compactness from logic of state-space model description and quantitativity from probabilistic knowledge of stochastic disturbances have been exploited to construct a situational awareness which then provides essential common knowledge to noncooperative decision makers about the adverse and dynamic environment within a linear-quadratic class of nonzero-sum stochastic games. It incorporates the perception of relevant attributes of the decision problem, comprehension of the meaning of the shared interaction model in combination with and in relation to various goals of non-cooperative decision makers so that future projection of higher-order characteristics of the Chi-squared random measures of performance is obtained with high confidence. New solution concepts, called the multi-cumulant Nash strategies are proposed to directly influence respective performance distributions and to effectively guarantee performance robustness for non-cooperative decision makers.