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    Strategies for Two Alternative Forced Choice Navigation Tasks

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    Author
    Lei, Henry
    Issue Date
    2020
    Keywords
    Model Predictive Control
    Signal Processing
    Stochastic Systems
    Advisor
    Reverdy, Paul B.
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    In the engineering community, there has been a growing interest in emulating robust continuous decision mechanisms, often found implicitly in biological systems, in engineered autonomous systems. The Two Alternative Forced Choice navigation problem, where an agent is required to decide between two possible navigation tasks based on a noisy signal, is a natural model problem for studying such mechanisms. In this thesis, we aim to generate and systematically study a variety of decision-making strategies in terms of the expected time, distance and error rates. We look at five in particular; the first four are preliminary, based off of various heuristics, while the fifth follows a model predictive control framework with a novel adaptive cost function that penalizes the control magnitude and deviation from a dynamic “artificial” goal. The strategies are studied using a variety of computational and analytic methods; for the model predictive control strategy in particular, closed form results for the expected trajectory in both deterministic and stochastic environments are presented.
    Type
    text
    Electronic Thesis
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Graduate College
    Mechanical Engineering
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

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