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In this paper we consider the problem of determining optimal decentralized decision rules in discrete stochastic decision problems. Here we consider a static single-stage problem. It has been shown in...
In this paper we consider Markov decision processes with average cost criteria, and discuss an approach for characterizing the performance loss associated with using a suboptimal control policy. Becau...
we consider the problem of computing decentralized control policies for stochastic systems with finite state and action spaces. Synthesis of optimal decentralized policies for such problems is known t...
While peer-to-peer consensus algorithms have enviable robustness and locality for distributed estimation and computation problems, they have poor scaling behavior with network diameter. We show how de...
arrsive algorithms where random observations enter are studied in a fairly general framework. An important feature is that the observations may depend on previous “outputs” of the algorithm. The consi...
Rearrsive algorithms where random observations enter are studied in a fairly general framework. An important feature is that the observations may depend on previous “outputs” of the algorithm. The con...
Distributed consensus and other linear systems with system stochastic matrices $W_k$ emerge in various settings, like opinion formation in social networks, rendezvous of robots, and distributed infere...
Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how...
The stochastic optimal control is an important research subject in structural engineering. Recently, a stochastic optimal nonlinear control method has been proposed based on the stochastic dynamical ...
One of the difficults for fault detection techniques for non-linear stochastic systems via model-based methods is the design of residual generation. In this paper, a new fault detection (FD) approche ...
A method consisting of auto-regressive approximation in system identification and input normal realization truncation in model reduction is proposed for transfer function identification of infinite-di...
Pollution is introduced into the utility function and the productive function in this paper. Under appropriate macroeconomic equilibrium conditions, this paper proves that the equilibrium levels of th...
In this paper, we use the solutions of forward-backward stochastic differentialequations to get the explicit form of the optimal control for linear quadraticstochastic optimal control problem and the ...
The optimal control problem of fully coupled forward-backward stochastic systems is put forward. A necessary condition, called maximum principle, for an optimal control of the problem with the control...
Let X_i, Y_j, i, j = 2…, n, be independent nonnegative r.v.'s with X_i~ F_i(t) = 1-exp(-R_i(t)) and Y_j~ G_j(t) = 1- exp(-R(t)), j=1,…, n. Two kinds of models are considered, and the monotone coupling...

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