Artificial Intelligence|教育線上App不用買

This unique free application is useful for all students of Artificial Intelligence across the world. It covers 142 topics of Artificial Intelligence in detail. These 142 topics are divided in 5 units.

Each topic is around 600 words and is complete with diagrams, equations and other forms of graphical representations along with simple text explaining the concept in detail.

The USP of this application is "ultra-portability". Students can access the content on-the-go from any where they like.

Basically, each topic is like a detailed flash card and will make the lives of students simpler and easier.

Some of topics Covered in this application are:

1. Turing test

2. Introduction to Artificial Intelligence

3. History of AI

4. The AI Cycle

5. Knowledge Representation

6. Typical AI problems

7. Limits of AI

8. Introduction to Agents

9. Agent Performance

10. Intelligent Agents

11. Structure Of Intelligent Agents

12. Types of agent program

13. Goal based Agents

14. Utility-based agents

15. Agents and environments

16. Agent architectures

17. Search for Solutions

18. State Spaces

19. Graph Searching

20. A Generic Searching Algorithm

21. Uninformed Search Strategies

22. Breadth-First Search

23. Heuristic Search

24. A∗ Search

25. Search Tree

26. Depth first Search

27. Properties of Depth First Search

28. Bi-directional search

29. Search Graphs

30. Informed Search Strategies

31. Methods of Informed Search

32. Greedy Search

33. Proof of Admissibility of A*

34. Properties of Heuristics

35. Iterative-Deepening A*

36. Other Memory limited heuristic search

37. N-Queens eample

38. Adversarial Search

39. Genetic Algorithms

40. Games

41. Optimal decisions in Games

42. minimax algorithm

43. Alpha Beta Pruning

44. Backtracking

45. Consistency Driven Techniques

46. Path Consistency (K-Consistency)

47. Look Ahead

48. Propositional Logic

49. Syntax of Propositional Calculus

50. Knowledge Representation and Reasoning

51. Propositional Logic Inference

52. Propositional Definite Clauses

53. Knowledge-Level Debugging

54. Rules of Inference

55. Soundness and Completeness

56. First Order Logic

57. Unification

58. Semantics

59. Herbrand Universe

60. Soundness, Completeness, Consistency, Satisfiability

61. Resolution

62. Herbrand Revisited

63. Proof as Search

64. Some Proof Strategies

65. Non-Monotonic Reasoning

66. Truth Maintenance Systems

67. Rule Based Systems

68. Pure Prolog

69. Forward chaining

70. backward Chaining

71. Choice between forward and backward chaining

72. AND/OR Trees

73. Hidden Markov Model

74. Bayesian networks

75. Learning Issues

76. Supervised Learning

77. Decision Trees

78. Knowledge Representation Formalisms

79. Semantic Networks

80. Inference in a Semantic Net

81. Extending Semantic Nets

82. Frames

83. Slots as Objects

84. Interpreting frames

85. Introduction to Planning

86. Problem Solving vs. Planning

87. Logic Based Planning

88. Planning Systems

89. Planning as Search

90. Situation-Space Planning Algorithms

91. Partial-Order Planning

92. Plan-Space Planning Algorithms

93. Interleaving vs. Non-Interleaving of Sub-Plan Steps

94. Simple Sock/Shoe Example

95. Probabilistic Reasoning

96. Review of Probability Theory

97. Semantics of Bayesian Networks

98. Introduction to Learning

99. Taxonomy of Learning Systems

100. Mathematical formulation of the inductive learning problem

101. Concept Learning

102. Concept Learning as Search

103. Algorithm to Find a Maximally-Specific Hypothesis

104. Candidate Elimination Algorithm

105. The Candidate-Elimination Algorithm

106. Decision Tree Construction

107. Splitting Functions

108. Decision Tree Pruning

109. Neural Networks

110. Artificial Neural Networks

111. Perceptron

112. Perceptron Learning

113. Multi-Layer Perceptrons

114. Back-Propagation Algorithm

115. Statistical learning

All topics not listed here because of character limit set by Play Store

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