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Filtering by: Creator Billman, Eric J. Remove constraint Creator: Billman, Eric J. Advisor Tumer, Kagan Remove constraint Advisor: Tumer, Kagan Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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  • Multiagent learning for locomotion and coordination in tensegrity robotics

    Creator:
    Iscen, Atil
    Abstract:
    Tensegrity structures are composed of pure compressional elements that are connected via a network of pure tensional elements. The concept of tensegrity promises numerous advantages to the field of robotics. Tensegrity robots are, however, notoriously difficult to control due to their oscillatory nature and nonlinear interaction between the components. Multiagent...
    Resource Type:
    Dissertation
    Full Text:
    reward function. We take a snapshot of the environment (z), feed the reward function with z and z−j

  • Using RUBI to partition agents in air traffic problems with hard constraints and reward shaping

    Creator:
    Curran, William
    Abstract:
    Air traffic flow management over the U.S. airpsace is a difficult problem. Current management approaches lead to hundreds of thousands of hours of delay, costing billions of dollars annually. Weather and airport conditions may instigate this delay, but routing decisions balancing delay with congestion contribute significantly to the propagation of...
    Resource Type:
    Masters Thesis
    Full Text:
    is set to 0. SIM(dn, di) and SIM(i, m, j) are functions computing the similarity between clus­

  • Learning-based Control of Experimental Hybrid Fuel Cell Power Plant

    Creator:
    Gabler, Andrew
    Abstract:
    Direct red Solid Oxide Fuel Cell (SOFC) Turbine hybrid plants have the potential to dramatically increase power plant efficiency, decrease emissions, and provide fast response to transient loads. The US Department of Energy's (DOE) Hybrid Performance Project is an experimental hybrid SOFC plant, built at the National Energy Technology Laboratory...
    Resource Type:
    Masters Thesis
    Full Text:
    weight of a network is given by: ∆wij = −α ∂E ∂wij = −αδjxi + η∆wt−1ij (2.3) δj =  (outputj