William W. Cohen's Papers: Explanation-Based Learning

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  1. William W. Cohen, Russell Greiner, and Dale Schuurmans (1994): Probabilistic hill-climbing in Computational learning theory and natural learning systems (Volume II), MIT Press..
  2. William W. Cohen (1994): Incremental abductive EBL in Machine Learning 15(1): 5-24 (1994).
  3. William W. Cohen (1994): Grammatically biased learning: learning logic programs using an explicit antecedent description language in Artif. Intell. 68(2): 303-366 (1994).
  4. William W. Cohen (1992): Using distribution-free learning theory to analyze solution path caching mechanisms in Computational Intelligence 8: 336-375 (1992).
  5. William W. Cohen (1992): Desiderata for generalization-to-n algorithms in AII 1992: 140-150.
  6. William W. Cohen (1992): Compiling prior knowledge into an explicit bias in ICML 1992: 102-110.
  7. William W. Cohen (1992): Abductive explanation based learning: A solution to the multiple inconsistent explanation problem in Machine Learning 8: 167-219 (1992).
  8. William W. Cohen (1993): A Review of `Creating a Memory of Causal Relationships' by Michael Pazzani in Machine Learning (1993).
  9. William W. Cohen (1991): The generality of overgenerality in ICML 1991: 490-494.
  10. William W. Cohen (1990): Learning from textbook knowledge: A case study in AAAI 1990: 743-748.
  11. William W. Cohen (1990): Learning approximate control rules of high utility in ICML 1990: 268-276.
  12. William W. Cohen (1990): An analysis of representation shift in concept learning in ICML 1990: 104-112.
  13. William W. Cohen (1990): Learning from Examples and an "Abductive Theory" in Proc. of the 1990 AAAI Spring Symposium on Abduction.
  14. William W. Cohen (1988): Generalizing number and learning from multiple examples in explanation-based learning in ICML 1988: 256-269.
  15. William W. Cohen, Jack Mostow & Alex Borgida (1988): Generalizing number in explanation-based learning in Proc. of the 1988 AAAI Spring Symposium on Explanation-Based Learning.

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