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Large problems are usually solved by first breaking them up into a set of smaller problems. It is also useful to know where to go to find methods, algorithms, etc. that may be useful in your AI work. No list of subfields is ever complete and unique but here is one I use:

1. weak methods

2. search

3. rule based systems

4. semantic networks

5. logic/deduction systems

6. heuristics

7. discovery/creativity/induction

8. natural language

9. neural networks

10. distributed AI/collective intelligence

11. robotics/embodiment

12. compression

13. automata/state machines

14. statistics

15. Bayesian statistics

16. planning/scheduling

17. case-based reasoning/memory-based reasoning

18. blackboard systems

19. nonstandard logics (including temporal logic)

20. representation

21. consciousness

22. learning/data mining

23. theorem proving

24. automatic programming

25. genetic programming

26. qualitative reasoning

27. constraint-based reasoning

28. agents

29. fuzzy logic

30. diagrammatic reasoning (including spatial logics)

31. model-based reasoning

32. emotion

33. ontology

34. quantum computing

35. analogy

36. parallel computing

37. pattern recognition/comparison

38. causality

39. deductive databases

40. language of thought

41. artificial life

42. philosophy of AI and mind

43. innateness/instinct

44. AI languages

45. memory/databases

46. decision theory

47. cognitive science

48. control system theory

49. digital electronics/hardware

50. dynamical systems

51. self-organizing systems

52. perception/vision/image manipulation

53. architectures

54. complexity theory

55. emergence

56. brain modeling

57. modularity

58. hybrid AI

59. optimization

60. goal-oriented systems

61. feature extraction/detection

62. utility/values/fitness/progress

63. multivariate function approximation

64. formal grammars and languages

65. theory of computation

66. classifiers/concept formation

67. theory of problem solving

68. artificial immune systems

69. curriculum for learners

70. speech recognition

71. theory of argumentation/informal logic

72. common sense reasoning

73. coherence/consistency

74. relevance/sensitivity analysis

75. semiotics

76. machine translation

77. pattern theory

78. operations research

79. game theory

80. automation

81. behaviorism

82. knowledge engineering

83. semantic web

84. sorting/typology/taxonomy

85. extrapolation/forecasting/interpolation/generalization

86. cooperation theory

87. systems theory

There is, of course, lots of overlap between these. Some are, of course, more fundamental to AI than others.

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13y ago

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