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    AAAI
    1996
    123views Intelligent Agents» more  AAAI 1996»
    Incorporating Opponent Models into Adversary Search
    14 years 11 months ago
    Incorporating Opponent Models into Adversary Search
    Download  www.cs.technion.ac.il
    This work presents a generalized theoretical framework that allows incorporation of opponent models into adversary search. We present the M algorithm, a generalization of minimax ...
    David Carmel, Shaul Markovitch
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    AAAI
    1996
    88views Intelligent Agents» more  AAAI 1996»
    On the Foundations of Qualitative Decision Theory
    14 years 11 months ago
    On the Foundations of Qualitative Decision Theory
    Download  www.aaai.org
    This paper investigates the foundation of rnaxipnin, one of the central qualitative decision criteria, using the approach taken by Savage (Savage 1972) to investigate the foundati...
    Ronen I. Brafman, Moshe Tennenholtz
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    AAAI
    1996
    101views Intelligent Agents» more  AAAI 1996»
    Nearly Monotonic Problems: A Key to Effective FA/C Distributed Sensor Interpretation?
    14 years 11 months ago
    Nearly Monotonic Problems: A Key to Effective FA/C Distributed Sensor Interpretation?
    Download  www.aaai.org
    The fesractioncslly-Qcczdrrcate, cooperative (FA/C) distributed problem-solving paradigm is one approach for organizing distributed problem solving among homogeneous, cooperating ...
    Norman Carver, Victor R. Lesser, Robert Whitehair
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    AAAI
    1996
    101views Intelligent Agents» more  AAAI 1996»
    Agent Cooperation Can Compensate For Agent Ignorance in Constraint Satisfaction
    14 years 11 months ago
    Agent Cooperation Can Compensate For Agent Ignorance in Constraint Satisfaction
    Download  www.aaai.org
    A team of constraint agents with diverse viewpoints canfind a solution to a constraint satisfaction problem (CSP) whenthe individual agents have an incomplete viewof the problem.I...
    Peggy S. Eaton, Eugene C. Freuder
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    AAAI
    1996
    150views Intelligent Agents» more  AAAI 1996»
    Irrelevance and Conditioning in First-Order Probabilistic Logic
    14 years 11 months ago
    Irrelevance and Conditioning in First-Order Probabilistic Logic
    Download  www.cs.cornell.edu
    First-order probabilistic logic is a powerful knowledge representation language. Unfortunately, deductive reasoning based on the standard semantics for this logic does not support...
    Daphne Koller, Joseph Y. Halpern
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