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    JIKM
    2008
    168views more  JIKM 2008»
    A Framework for Developing and Aligning a Knowledge Management Strategy
    13 years 7 months ago
    A Framework for Developing and Aligning a Knowledge Management Strategy
    Download  lpis.csd.auth.gr
    Businesses today, including non-profits, recognise the need for knowledge management (KM). KM may require new strategies and goals before it can be implemented, or it can be aligne...
    Deborah E. Swain, Jean-Pierre Booto Ekionea
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    ICML
    2008
    IEEE
    135views Machine Learning» more  ICML 2008»
    Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
    14 years 8 months ago
    Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
    Download  mapleleaf.csail.mit.edu
    Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
    Finale Doshi, Joelle Pineau, Nicholas Roy
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    COLING
    1990
    99views Computational Linguistics» more  COLING 1990»
    Three Typed Pragmatics for Dialogue Structure Analysis
    13 years 9 months ago
    Three Typed Pragmatics for Dialogue Structure Analysis
    Download  acl.ldc.upenn.edu
    An experimental system for dialogue structure analysis based on a new type plan recognition model for spoken dialogues has been implemented. This model is realized by using four t...
    Hitoshi Iida, Takayuki Yamaoka, Hidekazu Arita
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    RAS
    2006
    111views more  RAS 2006»
    Planning under uncertainty using model predictive control for information gathering
    13 years 7 months ago
    Planning under uncertainty using model predictive control for information gathering
    Download  services.eng.uts.edu.au
    This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered withi...
    Cindy Leung, Shoudong Huang, Ngai Ming Kwok, Gamin...
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    ATAL
    2010
    Springer
    171views Intelligent Agents» more  ATAL 2010»
    Closing the learning-planning loop with predictive state representations
    13 years 9 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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