Abstract-- We introduce a distributed estimation algorithm for use by a collection of stochastically interacting agents. Each agent has both a discrete value and an estimate of the...
Stochastic programming problems appear as mathematical models for optimization problems under stochastic uncertainty. Most computational approaches for solving such models are base...
Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to wh...
Jay Smith, Luis Diego Briceno, Anthony A. Maciejew...
— Piecewise linear Lyapunov functions are used to design control gain matrices so that closed systems are robust stable and attractive regions are expanded as large as possible i...
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...