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    AAAI
    2000
    99views Intelligent Agents» more  AAAI 2000»
    A* with Partial Expansion for Large Branching Factor Problems
    14 years 24 days ago
    A* with Partial Expansion for Large Branching Factor Problems
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    Takayuki Yoshizumi, Teruhisa Miura, Toru Ishida
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    AAAI
    2000
    120views Intelligent Agents» more  AAAI 2000»
    Interactive Training for Synthetic Characters
    14 years 24 days ago
    Interactive Training for Synthetic Characters
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    Compelling synthetic characters must behave in ways that reflect their past experience and thus allow for individual personalization. We therefore need a method that allows charac...
    Song-Yee Yoon, Robert C. Burke, Bruce Blumberg, Ge...
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    AAAI
    2000
    118views Intelligent Agents» more  AAAI 2000»
    Robust Combinatorial Auction Protocol against False-Name Bids
    14 years 24 days ago
    Robust Combinatorial Auction Protocol against False-Name Bids
    Download  www.aaai.org
    This paper presents a new combinatorial auction protocol (LDS protocol) that is robust against false-name bids. Internet auctions have become an integral part of Electronic Commer...
    Makoto Yokoo, Yuko Sakurai, Shigeo Matsubara
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    AAAI
    2000
    193views Intelligent Agents» more  AAAI 2000»
    Depth-First Branch-and-Bound versus Local Search: A Case Study
    14 years 24 days ago
    Depth-First Branch-and-Bound versus Local Search: A Case Study
    Download  www.aaai.org
    Depth-first branch-and-bound (DFBnB) is a complete algorithm that is typically used to find optimal solutions of difficult combinatorial optimization problems. It can also be adap...
    Weixiong Zhang
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    AAAI
    2000
    180views Intelligent Agents» more  AAAI 2000»
    Conceptual Indexing: Practical Large-Scale AI for Efficient Information Access
    14 years 24 days ago
    Conceptual Indexing: Practical Large-Scale AI for Efficient Information Access
    Download  www.aaai.org
    Finding information is a problem shared by people and intelligent systems. This paper describes an experiment combining both human and machine aspects in a knowledgebased system t...
    William A. Woods
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    AAAI
    2000
    120views Intelligent Agents» more  AAAI 2000»
    Multi-Fidelity Robotic Behaviors: Acting with Variable State Information
    14 years 24 days ago
    Multi-Fidelity Robotic Behaviors: Acting with Variable State Information
    Download  www.cs.cmu.edu
    Our work is driven by one of the core purposes of artificial intelligence: to develop real robotic agents that achieve complex high-level goals in real-time environments. Robotic ...
    Elly Winner, Manuela M. Veloso
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    AAAI
    2000
    101views Intelligent Agents» more  AAAI 2000»
    MarketSAT: An Extremely Decentralized (but Really Slow) Algorithm for Propositional Satisfiability
    14 years 24 days ago
    MarketSAT: An Extremely Decentralized (but Really Slow) Algorithm for Propositional Satisfiability
    Download  ftp.eecs.umich.edu
    We describe MarketSAT, a highly decentralized, marketbased algorithm for propositional satisfiability. The approach is based on a formulation of satisfiability as production on a ...
    William E. Walsh, Michael P. Wellman
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    AAAI
    2000
    115views Intelligent Agents» more  AAAI 2000»
    Learning Subjective Adjectives from Corpora
    14 years 24 days ago
    Learning Subjective Adjectives from Corpora
    Download  www.cs.pitt.edu
    Janyce Wiebe
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    AAAI
    2000
    81views Intelligent Agents» more  AAAI 2000»
    Untangle: A New Ontology for Card Catalog Systems
    14 years 24 days ago
    Untangle: A New Ontology for Card Catalog Systems
    Download  www.aaai.org
    The ontology used by most card catalog and bibliographic systems is based on a now outdated assumption that users of the systems would be looking for books on shelves, and therefo...
    Christopher A. Welty, Jessica Jenkins
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    AAAI
    2000
    116views Intelligent Agents» more  AAAI 2000»
    A Quantitative Study of Small Disjuncts
    14 years 24 days ago
    A Quantitative Study of Small Disjuncts
    Download  storm.cis.fordham.edu
    Systems that learn from examples often express the learned concept in the form of a disjunctive description. Disjuncts that correctly classify few training examples are known as s...
    Gary M. Weiss, Haym Hirsh
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