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Filtering by: Creator Verbeeck, H. Remove constraint Creator: Verbeeck, H. Advisor Tumer, Kagan Remove constraint Advisor: Tumer, Kagan

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  • Learning from action not taken in multiagent systems

    Creator:
    Khani, Newsha
    Abstract:
    Coordination in large multiagent systems in order to achieve a system level goal is a critical challenge. Given the agents' intention to cooperate, there is no guarantee that the agent actions will lead to good system objective especially when the system becomes large. One of the primary difficulties in such...
    Resource Type:
    Masters Thesis
    Full Text:
    its expected reward for the next h-steps. In the next step, the model proposes the action resulting

  • 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