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Filtering by: Conference name ACRL Virtual Conference 2019 Remove constraint Conference name: ACRL Virtual Conference 2019 License Attribution 4.0 (CC BY 4.0) Remove constraint License: Attribution 4.0 (CC BY 4.0) Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Just a tool after all? No evidence for tool-use effects on the body representation across virtual and real environments

    Creator:
    Bell, Joshua D.
    Abstract:
    While human tool-use proficiency helped define our history, the cognitive and perceptual mechanics of how humans use tools are not fully understood. This question is of great value to the design of hand-held tools and prosthetics. A prominent theory, tool embodiment, suggests that tool use is facilitated by a flexible...
    Resource Type:
    Dissertation
    Full Text:
    psychology (Lanier et al., 2019). In addition to these potential visual shortcomings, virtual environments

  • Adaptive Learning Module for Introduction to Materials Science

    Creator:
    Nigon, Nutnicha
    Abstract:
    There is a growing need for individualized instructional designs in 4-year institutions due to: 1) growing undergraduate enrollment trends across the U.S., 2) broader diversity in students backgrounds, and 3) the growing prevalence of asynchronous remote learning. With the growth in computer technology in education, tools such as adaptive intelligent...
    Resource Type:
    Dissertation
    Full Text:
    , Melissa T. Penyai, and one Capstone team in 2019. In addition, I thank Katherine McAlvage, Susan M. Fein

  • On Avoiding Power-Seeking by Artificial Intelligence

    Creator:
    Turner, Alexander M.
    Abstract:
    We do not know how to align a very intelligent AI agent's behavior with human interests. I investigate whether—absent a full solution to this AI alignment problem—we can build smart {\ai} agents which have limited impact on the world, and which do not autonomously seek power. In this thesis, I...
    Resource Type:
    Dissertation
    Full Text:
    the AAAI/ACM Conference on AI, Ethics, and Society 2020 Abstract Reward functions are easy to