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    NECO
    2007
    87views more  NECO 2007»
    Reinforcement Learning State Estimator
    15 years 3 months ago
    Reinforcement Learning State Estimator
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    cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
    Jun Morimoto, Kenji Doya
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    162
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    AAAI
    2011
    202views Intelligent Agents» more  AAAI 2011»
    Value Function Approximation in Reinforcement Learning Using the Fourier Basis
    14 years 3 months ago
    Value Function Approximation in Reinforcement Learning Using the Fourier Basis
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    We describe the Fourier Basis, a linear value function approximation scheme based on the Fourier Series. We empirically evaluate its properties, and demonstrate that it performs w...
    George Konidaris, Sarah Osentoski, Philip Thomas
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    IJAMCIGI
    2010
    90views more  IJAMCIGI 2010»
    A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling
    15 years 29 days ago
    A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling
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    Hyper-heuristics are identified as the methodologies that search the space generated by a finite set of low level heuristics for solving difficult problems. One of the iterative h...
    Ender Özcan, Mustafa Misir, Gabriela Ochoa, E...
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    ICML
    2000
    IEEE
    147views Machine Learning» more  ICML 2000»
    Learning to Fly: An Application of Hierarchical Reinforcement Learning
    16 years 4 months ago
    Learning to Fly: An Application of Hierarchical Reinforcement Learning
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    Malcolm R. K. Ryan, Mark D. Reid
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    JAIR
    2000
    95views more  JAIR 2000»
    Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
    15 years 3 months ago
    Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
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    Thomas G. Dietterich
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