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Filtering by: Creator Kearns, Richard Seng Remove constraint Creator: Kearns, Richard Seng Advisor Tumer, Kagan Remove constraint Advisor: Tumer, Kagan Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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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:
    . Belinda Batten, Dr. Ross Hatton, Dr. Jonathan Hurst, Dr. Ravi Balasubramanian, and Dr. Richard Nafshun

  • Applying hierarchical and adaptive control to coordinating simple robots

    Creator:
    Knudson, Matthew D.
    Abstract:
    Coordinating multiple robots to achieve a complex task requires solving two distinct control problems: the high-level control problem of ensuring that each robot aims to perform a useful task (e.g., coordination) and the low-level control problem of ensuring that each robot actually performs the correct actions to achieve its task...
    Resource Type:
    Masters Thesis