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Abstruct-Fault detection and isolation is a crucial and challenging task in the automatic control of large complex systems. We propose a discrete-event system (DES) approach to the problem of failure diagnosis. We introduce two related notions of diagnosability of DES's in the framework of formal languages and compare diagnosability with the related notions(More)
We consider multiarmed bandit problems with switching cost, define uniformly good allocation rules, and restrict attention to such rules. We present a lower bound on the asymptotic performance of uniformly good allocation rules and construct an allocation scheme that achieves the bound. We discover that despite the inclusion of a switching cost the proposed(More)
Abstruct-We consider a controlled i.i.d. process whose distribution is parametrized by an unknown parameter 8 belonging to some known parameter space 8, and a one-step reward associated with each pair of control and the following state of the process. The objective is to maximize the expected value of the sum of one-step rewards over an infinite horizon. By(More)
We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of two local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosabil-ity, originally introduced in 1](More)
—We investigate a network routing problem where a probabilistic local broadcast transmission model is used to determine routing. We discuss this model's key features, and note that the local broadcast transmission model can be viewed as soft handoff for an ad-hoc network. We present results showing that an index policy is optimal for the routing problem. We(More)
—We investigate diagnosability of stochastic discrete event systems. We define the notions of A-and AA-diag-nosability for stochastic automata; these notions are weaker than the corresponding notion of diagnosability for logical automata introduced by Sampath et al. Through the construction of a stochastic diagnoser, we determine offline conditions(More)
1. Introduction Multi-armed bandit (MAB) problems are a class of sequential resource allocation problems concerned with allocating one or more resources among several alternative (competing) projects. Such problems are paradigms of a fundamental conflict between making decisions (allocating resources) that yield high current rewards, versus making decisions(More)
The output of a discrete-time Markov source must be encoded into a sequence of discrete variables. The encoded sequence is transmitted through a noisy channel to a receiver that must attempt to reproduce reliably the source sequence. Encoding and decoding must be done in real-time and the distortion measure does not tolerate delays. The structure of(More)
Two detectors making independent observations must decide which one of two hypotheses is true. The decisions are coupled through a common cost function. It is shown that the detectors' optimal decisions are characterized by thresholds which are coupled and whose computation requires the solution of two coupled sets of dynamic programming equations. An(More)