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Volume 6 Issue 4
October  1991
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Hayong Zhou. Analogical Learning and Automated Rule Constructions[J]. Journal of Computer Science and Technology, 1991, 6(4): 316-328.
Citation: Hayong Zhou. Analogical Learning and Automated Rule Constructions[J]. Journal of Computer Science and Technology, 1991, 6(4): 316-328.
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Analogical Learning and Automated Rule Constructions

  • Department of Computer & Information Sciences Towson State University; Towson MD 21204;

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  • Published Date: October 09, 1991
    Abstract
  • This paper describes some experiments of analogical learning and automated rule construction.The present investigation focuses on knowledge acquisition,learning by analogy,and knowledge retention. The developed system initially learns from scratch,gradually acquires knowledge from,its environment through trial-and-error interaction,incrementally augments its knowledge base,and analogically solves new tasks in a more efficient and direct manner.
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    • References (5)
  • [1]
    Booker.L.B., Intelligent behavior as adaptation to the task environment. Doctoral dissertation, Department Computer and Communication Sciences, University of Michigan. Ann Arbor MI. 1982.
    [2]
    Carbonell.J.G., Learning by analogy: Formulating and generalizing phans from past experience. In Machine Learning: An artificial intelligence approach, Tioga, Palo Alto. CA, 1983.
    [3]
    Holland.J.H., Adaptation in Natural and Artificial Systems. The University of Michigan Press, 1975.
    [4]
    Holland.J.H. and Reitman.J.S., Cognitive Systems Based on Adaptive Algorithms. Pattern-Directed Inference Systems. Academic Press. New York. 1978.
    [5]
    Holland.J.H., Escaping Brittleness: The Possibilities of General Purpose Learning Algorithms Applied to Parallel Rule-Based Systems .Machine Learning(II):593-623. Morgan Kaufrnann, 1986. ………..
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