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    AAAI
    2006
    199views Intelligent Agents» more  AAAI 2006»
    Decision Making in Uncertain Real-World Domains Using DT-Golog
    13 years 11 months ago
    Decision Making in Uncertain Real-World Domains Using DT-Golog
    Download  www.aaai.org
    DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
    Mikhail Soutchanski, Huy Pham, John Mylopoulos
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    MASCOTS
    2004
    132views Modeling And Simulation» more  MASCOTS 2004»
    An Optimisation Model for a Two-Node Router Network
    13 years 11 months ago
    An Optimisation Model for a Two-Node Router Network
    Download  pubs.doc.ic.ac.uk
    Architectural designs for routers and networks of routers to support mobile communication are analysed for their end-to-end performance using a simple Markov model. In view of the...
    Nalan Gülpinar, Peter G. Harrison, Berç...
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    WSC
    1997
    147views Modeling And Simulation» more  WSC 1997»
    Before Dynamic Simulation: Systematic Layout Design from Scratch
    13 years 11 months ago
    Before Dynamic Simulation: Systematic Layout Design from Scratch
    Download  www.informs-sim.org
    Excellent production design and planning depends on accurate simulation of a high quality layout. A good layout project will always begin with an analysis of the production volume...
    David P. Sly
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    NIPS
    1996
    110views Information Technology» more  NIPS 1996»
    Predicting Lifetimes in Dynamically Allocated Memory
    13 years 11 months ago
    Predicting Lifetimes in Dynamically Allocated Memory
    Download  www.eecs.umich.edu
    Predictions oflifetimesofdynamicallyallocated objects can be used to improve time and space e ciency of dynamic memory management in computer programs. Barrett and Zorn 1993] used...
    David A. Cohn, Satinder P. Singh
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    ATAL
    2010
    Springer
    171views Intelligent Agents» more  ATAL 2010»
    Closing the learning-planning loop with predictive state representations
    13 years 11 months ago
    Closing the learning-planning loop with predictive state representations
    Download  www.cs.cmu.edu
    A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
    Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
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