Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 106-108). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--Oregon State University, 1996. / Typescript (photocopy). Includes bibliographical references (leaves 68-69). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1973. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

This dissertation applies policy improvement and successive approximation or value iteration to a general class of Markov decision processes with discounted costs. In particular, a class of Markov decision processes, called piecewise-linear, is studied. Piecewise-linear processes are characterized by the property that the value function of a process observed for one period and then terminated is piecewise-linear if the terminal reward function is piecewise-linear. Partially observable Markov decision processes have this property. It is shown that there are e-optimal piecewise-linear value functions and piecewise-constant policies which are simple. Simple means that there are only finitely many pieces, each of which is defined on a convex polyhedral set. Algorithms based on policy improvement and successive approximation are developed to compute simple approximations to an optimal policy and the optimal value function. / Business, Sauder School of / Graduate

The (nonlinear) response behavior of a piecewise-linear system is investigated under both deterministic and stochastic excitations in this study. A semi-analytical procedure is developed to predict the system behavior by evaluating the joint probability density functions of the Fokker-Planck equations of the stochastic piecewise-linear system under random excitations via a path-integral solution procedure. From an analysis of the deterministic system, nonlinear system behavior is derived for further analysis of the corresponding stochastic system. The influence of variations in other parameters on the response behavior are also examined. In the stochastic system analysis, which represents a more realistic approach to understanding the system behavior, a Markov process approach is used. By introducing random perturbations in the harmonic excitation, the stochastic responses are examined and compared to those of the corresponding deterministic system. Stability of the various responses including regular and chaotic motions, is investigated by varying the noise intensity. Routes to chaos in period-doubling processes with and without external random perturbations are studied and compared. Stationarity and ergodicity of the chaotic responses of the system are examined via time domain and probability domain simulations. Potential coexisting responses of the piecewise-linear system are examined via the path-integral solutions. It is found that the path-integral solutions can provide global information of the system behavior in the probability domain, and can also verify the potential coexisting responses and discern the relative strength of the coexisting response attractors. / Graduation date: 1996

No description available.

Thesis (Ph. D.)--School of Industrial and Systems Engineering, Georgia Institute of Technology, 2004. Directed by George L. Nemhauser. / Vita. Includes bibliographical references (leaves 91-94).

No description available.

Thesis (M.S.)--Brigham Young University. Dept of Mathematics, 2006. / Includes bibliographical references (p. 30).

Thesis (M.S.)--Duquesne University, 2004. / Title from document title page. Abstract included in electronic submission form. Includes bibliographical references (p. 30).