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Association for the Advancement of Artificial Intelligence

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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 9 /

Learning

Learning and Evaluation Functions

  • Constructive Induction on Domain Information

    James P. Callan, Paul E. Utgoff

    PDF
  • Two Kinds of Training Information For Evaluation Function Learning

    Paul E. Utgoff, Jeffrey A. Clouse

    PDF
  • A Complexity Analysis of Cooperative Mechanisms in Reinforcement Learning

    Steven D. Whitehead

    PDF
  • Adaptive Pattern-Oriented Chess

    Robert Levinson, Richard Snyder

    PDF

Learning Connectionist Representations

  • Analysis of the Internal Representations in Neural Networks for Machine Intelligence

    Lai-Wan Chan

    PDF
  • Direct Transfer of Learned Information Among Neural Networks

    Lorien Y. Pratt, Jack Mostow, Candace A. Kamm

    PDF
  • Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs

    Thomas G. Dietterich, Ghulum Bakiri

    PDF
  • Rule Learning by Searching on Adapted Nets

    LiMin Fu

    PDF

Learning Search Control

  • Integrating Abstraction and Explanation-Based Learning in PRODIGY

    Craig A. Knoblock, Steven Minton, Oren Etzioni

    PDF
  • STATIC: A Problem-Space Compiler for PRODIGY

    Oren Etzioni

    PDF
  • SteppingStone: An Empirical and Analytical Evaluation

    David Ruby, Dennis Kibler

    PDF
  • Synthesizing UNIX Shell Scripts Using Derivational Analogy: An Empirical Assessment

    Sanjay Bhansali, Mehdi T. Harandi

    PDF

Learning Theory and MDL

  • A Minimal Encoding Approach to Feature Discovery

    Mark Derthick

    PDF
  • Analyses of Instance-Based Learning Algorithms

    Marc K. Albert, David W. Aha

    PDF
  • Learning with Many Irrelevant Features

    Hussein Almuallim, Thomas G. Dietterich

    PDF
  • Regularity and Structure

    Alexander Botta

    PDF

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