Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Baras, John S.Subject: search.filters.subject.dynamic programming

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    A Hierarchical Structure For Finite Horizon Dynamic Programming Problems
    (2000) Zhang, Chang; Baras, John S.; Baras, John S.; ISR; CSHCN
    In dynamic programming (Markov decision) problems, hierarchicalstructure (aggregation) is usually used to simplify computation. Most research on aggregation ofMarkov decision problems is limited to the infinite horizon case, which has good tracking ability. However, in reallife, finite horizon stochastic shortest path problems are oftenencountered.

    In this paper, we propose a hierarchical structure to solve finite horizon stochastic shortest pathproblems in parallel. In general, the approach reducesthe time complexity of the original problem to a logarithm level, which hassignificant practical meaning.

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    Intelligent Distributed Fault Management for Communication Networks
    (2000) Li, Hongjun; Baras, John S.; ISR; CSHCN
    In this paper, we present an intelligent, distributed fault management system for communication networks using belief networks as fault model and inference engine. The managed network is divided into domains and for each domain, there is an intelligent agent called Domain Diagnostic Agent attached to it, which is responsible for this domain's fault management. Belief network models are embedded in such an agent and under symptoms observation, the posterior probabilities of each candidate fault node being faulty is computed. We define the notion of right diagnosis, describe the diagnosis process based on this concept, and present a strategy for generation of test sequence.
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    Group Invariance and Symmetries in Nonlinear Control and Estimation
    (2000) Baras, John S.; ISR
    We consider nonlinear filtering problems, nonlinear robust control problems and the partial differential equations that characterize their solutions. These include the Zakai equation, and in the robust control case two coupled Dynamic Programming equations.

    We then characterize equivalence between two such problems when we can compute the solution of one from the solution of the other using change of dependent, independent variables and solving an ordinary differential equation.

    We characterize the resulting transformation groups via their Lie Algebras. We illustrate the relationship of these results to symmetries and invariances in physics, Noether's theorem, and calculus of variations.

    We show how using these techniques one can solve nonlinear problems by reduction to linear ones.

    Second Nonlinear Control Network (NCN) Workshop, June 5, 2000