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    ESANN
    2008
    278views Neural Networks» more  ESANN 2008»
    Learning to play Tetris applying reinforcement learning methods
    13 years 11 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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    ICAI
    2008
    134views Artificial Intelligence» more  ICAI 2008»
    Nonrestrictive Concept-Acquisition by Representational Redescription
    13 years 11 months ago
    Nonrestrictive Concept-Acquisition by Representational Redescription
    Download  paper.ijcsns.org
    coarse procedures or very abstract frames from the point of view of algorithm, because some crucial issues like the representation, evolution, storage, and learning process of conc...
    Hui Wei, Yan Chen
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    IUSED
    2008
    88views Software Engineering» more  IUSED 2008»
    Preparing Usability Supporting Architectural Patterns for Industrial Use
    13 years 11 months ago
    Preparing Usability Supporting Architectural Patterns for Industrial Use
    Download  www.cs.cmu.edu
    Usability supporting architectural patterns (USAPs) have been shown to provide developers with useful guidance for producing a software architecture design that supports usability...
    Pia Stoll, Bonnie E. John, Len Bass, Elspeth Golde...
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    OPODIS
    2007
    119views Distributed And Parallel Com...» more  OPODIS 2007»
    Small-World Networks: From Theoretical Bounds to Practical Systems
    13 years 11 months ago
    Small-World Networks: From Theoretical Bounds to Practical Systems
    Download  www.irisa.fr
    Abstract. In small-world networks, each peer is connected to its closest neighbors in the network topology, as well as to additional long-range contact(s), also called shortcut(s)....
    François Bonnet, Anne-Marie Kermarrec, Mich...
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    RSS
    2007
    136views Robotics» more  RSS 2007»
    The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
    13 years 11 months ago
    The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty
    Download  www.ieor.berkeley.edu
    — We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
    Ron Alterovitz, Thierry Siméon, Kenneth Y. ...
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