A Risk-Averse Game-Theoretic Approach to Distributed Control

The research article gives a comprehensive presentation of the broad and still developing area of risk-averse decision-making approach to control of distributed stochastic systems. A distributed stochastic system considered here consists of the interconnection of two or more stochastic systems with the structural constraints of linear system dynamics, quadratic cost functionals, and additive stationary Wiener noises corrupting the system dynamics and measurements. Each system has an input from its incumbent agent or controller and an output to its local environment, in addition to links with the other neighboring systems. The problem of distributed control without communications between incumbent agents or controllers is formulated as a nonzero-sum stochastic differential game. Local best responses by each incumbent agents with risk-averse attitudes toward performance uncertainty are determined by a person-by-person equilibrium and subject to decentralized output-feedback information structures.