Predicate invention adapted as a tool for logic program synthesis 新述語発明機構を用いた論理プログラムの合成

この論文をさがす

著者

    • Chowdhury Mofizur R コウドハリィ モフィザー

書誌事項

タイトル

Predicate invention adapted as a tool for logic program synthesis

タイトル別名

新述語発明機構を用いた論理プログラムの合成

著者名

Chowdhury Mofizur R

著者別名

コウドハリィ モフィザー

学位授与大学

東京工業大学

取得学位

博士 (学術)

学位授与番号

甲第3338号

学位授与年月日

1996-09-30

注記・抄録

博士論文

目次

  1. 論文目録 / (0001.jp2)
  2. Contents / p2 (0005.jp2)
  3. 1 Introduction / p1 (0010.jp2)
  4. 1.1 Inductive Logic Programming / p1 (0010.jp2)
  5. 1.2 An Outline of the Research / p5 (0014.jp2)
  6. 1.3 Organization of the Thesis / p6 (0015.jp2)
  7. 2 Previous works / p8 (0017.jp2)
  8. 2.1 ILP Learning Algorithms / p8 (0017.jp2)
  9. 2.2 Constructive Induction in ILP / p18 (0027.jp2)
  10. 3 Overview of ALPS / p23 (0032.jp2)
  11. 3.1 Definitions / p23 (0032.jp2)
  12. 3.2 Input and Output / p25 (0034.jp2)
  13. 3.3 ALPS: A Covering Algorithm / p28 (0037.jp2)
  14. 4 Simulating Predicate Invention in Top-down Search / p31 (0040.jp2)
  15. 4.1 Predicate Invention and Top-down Induction / p31 (0040.jp2)
  16. 4.2 Simulating the Argument Selection Heuristics in Top-down Search / p35 (0044.jp2)
  17. 5 Dynamic Bias Shift Across Hierarchical Subspaces / p44 (0053.jp2)
  18. 5.1 Hierarchical Hypothesis Subspaces / p44 (0053.jp2)
  19. 5.2 Progressive Bias Adjustments in Top-down Search / p47 (0056.jp2)
  20. 5.3 Some Useful Techniques to Prune the Search Space / p50 (0059.jp2)
  21. 5.4 ALPS at a Glance / p51 (0060.jp2)
  22. 6 Experiments with ALPS / p55 (0064.jp2)
  23. 6.1 Learning Logic Programs / p55 (0064.jp2)
  24. 6.2 Learning in an Uncomfortable Situation / p62 (0071.jp2)
  25. 6.3 Effectiveness of Fixing Appropriate Bias / p68 (0077.jp2)
  26. 7 Integrating the Proposed Techniques to Existing System / p70 (0079.jp2)
  27. 7.1 Introduction to NFOIL / p70 (0079.jp2)
  28. 7.2 Algorithmic Description of NFOIL / p71 (0080.jp2)
  29. 7.3 Comparison between FOIL and NFOIL / p75 (0084.jp2)
  30. 7.4 Analytical Comparison / p80 (0089.jp2)
  31. 8 Using ALPS to Learn from Incomplete Training Set / p83 (0092.jp2)
  32. 8.1 The Learning Problem and Recent Approaches / p83 (0092.jp2)
  33. 8.2 A Different Learning Approach / p86 (0095.jp2)
  34. 8.3 Preprocessing Procedure / p88 (0097.jp2)
  35. 8.4 The Extended ALPS System / p94 (0103.jp2)
  36. 9 Conclusion / p101 (0110.jp2)
  37. A Training Data for the Experiments of Table 6.1 / p111 (0120.jp2)
  38. B Background Predicates of Table 6.5 / p114 (0123.jp2)
  39. C Sample Run / p134 (0143.jp2)
  40. C.1 Learning qsort/2 of Table 6.2 / p134 (0143.jp2)
  41. C.2 Learning delf/3 of Table 6.5 / p137 (0146.jp2)
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各種コード

  • NII論文ID(NAID)
    500000153540
  • NII著者ID(NRID)
    • 8000000153811
  • DOI(NDL)
  • NDL書誌ID
    • 000000317854
  • データ提供元
    • NDL-OPAC
    • NDLデジタルコレクション
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