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The interaction of interest-coupled decision-makers and the uncertainty of individual behavior are prominent characteristics of multiagent systems (MAS). How to break through the framework of conventional control theory, which aims at single decision-maker and single decision objective, and to extend the methodology and tools in the stochastic adaptive control theory to analyze MAS are of great significance...
We consider the decentralized control for a class of stochastic multi-agent systems described by coupled first order auto-regression models with exogenous inputs (ARX models). A stochastic time-averaged group-tracking-like performance index is adopted for each agent, with which the individual and population average states are coupled nonlinearly. A decentralized control law is designed based on the...
The concept of asymptotic Nash-equilibria with respect to stochastic performance index is introduced, a decentralized control law is constructed for large population dynamic multi-agent systems (LPDMAS) with cost-coupled stochastic performance indexes by using the state aggregation method. By the limit probability theory, it is shown that the closed-loop system is almost surely uniformly stable, and...
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