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  • A mathematical modeling framework for scheduling and managing multiple concurrent tasks

    Creator:
    Shakeri, Shakib
    Abstract:
    Occurrence of human error in highly complex systems, such as a cockpit, can be disastrous and/or overwhelmingly costly. Mismanagement of multiple concurrent tasks has been observed by researchers to be a type of repetitive human error in previous studies of accidents and incidents. This error may occur in the form...
    Resource Type:
    Dissertation
    Full Text:
    decision-making process. The measure of performance, which is widely considered in previous research as

  • Just enough die-level functional test : optimizing IC test via machine learning and decision theory

    Creator:
    Fountain, Tony R.
    Abstract:
    This research explores the hypothesis that methods from decision theory and machine learning can be combined to provide practical solutions to current manufacturing control problems. This hypothesis is explored by developing an integrated approach to solving one manufacturing problem - the optimization of die-level functional test. An integrated circuit (IC)...
    Resource Type:
    Dissertation
    Full Text:
    machine learning and decision theory AN ABSTRACT OF THE THESIS OF Tony R. Fountain for the degree of

  • Effective decision-theoretic assistance through relational hierarchical models

    Creator:
    Natarajan, Sriraam
    Abstract:
    Building intelligent computer assistants has been a long-cherished goal of AI. Many intelligent assistant systems were built and fine-tuned to specific application domains. In this work, we develop a general model of assistance that combines three powerful ideas: decision theory, hierarchical task models and probabilistic relational languages. We use the...
    Resource Type:
    Dissertation
    Full Text:
    Sriraam Natarajan for the degree of Doctor of Philosophy in Computer Science presented on November 20

  • Adiabatic Markov Decision Process : convergence of value iteration algorithm

    Creator:
    Duong, Thai
    Abstract:
    Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
    Resource Type:
    Masters Thesis
    Full Text:
    ) is a well-known framework for devising the opti­ mal decision making strategies under uncertainty

  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    decision making problems with uncertainty, ranging from classical problems such as in- ventory control and