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Filtering by: Creator Agogino, Adrian Remove constraint Creator: Agogino, Adrian Committee Member Hurst, Jonathan Remove constraint Committee Member: Hurst, Jonathan Decade 2010-2019 Remove constraint Decade: 2010-2019

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  • CLEAN learning to improve coordination and scalability in multiagent systems

    Creator:
    HolmesParker, Chris
    Abstract:
    Recent advances in multiagent learning have led to exciting new capabilities spanning fields as diverse as planetary exploration, air traffic control, military reconnaissance, and airport security. Such algorithms provide a tangible benefit over traditional control algorithms in that they allow fast responses, adapt to dynamic environments, and generally scale well....
    Resource Type:
    Dissertation
    Full Text:
    , Billy Bloudek, Adrian Agogino, and Orville Holmes. The support, advice, and help I have received from

  • Combining coordination mechanisms to improve performance in multi-robot teams

    Creator:
    Nasroullahi, Ehsan
    Abstract:
    Coordination is essential to achieving good performance in cooperative multiagent systems. To date, most work has focused on either implicit or explicit coordination mechanisms, while relatively little work has focused on the benefits of combining these two approaches. In this work we demonstrate that combining explicit and implicit mechanisms can...
    Resource Type:
    Masters Thesis