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    AAAI
    2006
    127views Intelligent Agents» more  AAAI 2006»
    Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
    15 years 4 months ago
    Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
    Download  robotic.media.mit.edu
    As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
    Andrea Lockerd Thomaz, Cynthia Breazeal
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    ESANN
    2008
    278views Neural Networks» more  ESANN 2008»
    Learning to play Tetris applying reinforcement learning methods
    15 years 4 months ago
    Learning to play Tetris applying reinforcement learning methods
    Download  www.dice.ucl.ac.be
    In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
    Alexander Groß, Jan Friedland, Friedhelm Sch...
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    136
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    SIGGRAPH
    2010
    ACM
    295views Computer Graphics» more  SIGGRAPH 2010»
    Learning behavior styles with inverse reinforcement learning
    15 years 7 months ago
    Learning behavior styles with inverse reinforcement learning
    Download  grail.cs.washington.edu
    We present a method for inferring the behavior styles of character controllers from a small set of examples. We show that a rich set of behavior variations can be captured by dete...
    Seong Jae Lee, Zoran Popovic
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    129
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    NIPS
    2001
    101views Information Technology» more  NIPS 2001»
    Reinforcement Learning with Long Short-Term Memory
    15 years 4 months ago
    Reinforcement Learning with Long Short-Term Memory
    Download  staff.science.uva.nl
    This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage learning and directed exploration can...
    Bram Bakker
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    NIPS
    2001
    121views Information Technology» more  NIPS 2001»
    Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
    15 years 4 months ago
    Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
    Download  books.nips.cc
    We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
    Gregory Z. Grudic, Lyle H. Ungar
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