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    IAT
    2010
    IEEE
    141views Intelligent Agents» more  IAT 2010»
    Getting What You Pay For: Is Exploration in Distributed Hill Climbing Really Worth it?
    13 years 7 months ago
    Getting What You Pay For: Is Exploration in Distributed Hill Climbing Really Worth it?
    Download  www.personal.utulsa.edu
    Abstract--The Distributed Stochastic Algorithm (DSA), Distributed Breakout Algorithm (DBA), and variations such as Distributed Simulated Annealing (DSAN), MGM-1, and DisPeL, are di...
    Melanie Smith, Roger Mailler
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    AIL
    2008
    109views more  AIL 2008»
    Artificial institutions: a model of institutional reality for open multiagent systems
    13 years 10 months ago
    Artificial institutions: a model of institutional reality for open multiagent systems
    Download  doc.rero.ch
    Software agents' ability to interact within different open systems, designed by different groups, presupposes an agreement on an unambiguous definition of a set of concepts, ...
    Nicoletta Fornara, Francesco Viganò, Mario ...
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    AAAI
    2007
    122views Intelligent Agents» more  AAAI 2007»
    Predictive Exploration for Autonomous Science
    14 years 4 days ago
    Predictive Exploration for Autonomous Science
    Download  www.aaai.org
    Often remote investigations use autonomous agents to observe an environment on behalf of absent scientists. Predictive exploration improves these systems’ efficiency with onboa...
    David R. Thompson
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    AAAI
    2006
    81views Intelligent Agents» more  AAAI 2006»
    Strategy Variations in Analogical Problem Solving
    13 years 11 months ago
    Strategy Variations in Analogical Problem Solving
    Download  www.qrg.northwestern.edu
    While it is commonly agreed that analogy is useful in human problem solving, exactly how analogy can and should be used remains an intriguing problem. VanLehn (1998) for instance ...
    Tom Y. Ouyang, Kenneth D. Forbus
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    AAAI
    1996
    127views Intelligent Agents» more  AAAI 1996»
    A Complexity Analysis of Space-Bounded Learning Algorithms for the Constraint Satisfaction Problem
    13 years 11 months ago
    A Complexity Analysis of Space-Bounded Learning Algorithms for the Constraint Satisfaction Problem
    Download  www.cs.sfu.ca
    Learning during backtrack search is a space-intensive process that records information (such as additional constraints) in order to avoid redundant work. In this paper, we analyze...
    Roberto J. Bayardo Jr., Daniel P. Miranker
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