Artificial Intelligence

The app is a complete free handbook of Artificial Intelligence with diagrams and graphs. It is part of Computer science or software engineering education which brings important topics, notes, news & blog on the subject. The App serves as a quick reference guide on this engineering subject.

It covers more than 600 topics of Artificial Intelligence, Automata, Real-time systems & Neuro fuzzy in detail. The topics are divided into 5 units.

Each topic is complete with diagrams, equations and other forms of graphical representations for better learning and quick understanding. The App will provide faster learning and quick revisions on the subject.

Few Additional subjects which have been included in the app are

Automata

Neural network fuzzy systems

Real-time Systems

Some of the 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

AI is going to be one of the most important technologies in the coming days. It is a must have study for engineering, computer science, software engineering and other cognitive science students. It also going to be extremely important for mechanical, Automotive & electrical engineering students and Professionals.

Download the app for the introduction to AI and related technology.

Aplikasi ini adalah sebuah buku panduan percuma lengkap Kepintaran Buatan dengan gambar rajah dan graf. Ia adalah sebahagian daripada sains komputer atau pendidikan kejuruteraan perisian yang membawa topik penting, nota, berita & blog mengenai subjek ini. App berfungsi sebagai panduan mudah kepada kejuruteraan perkara ini.

Ia meliputi lebih daripada 600 topik Kepintaran Buatan, Automata, sistem masa nyata & Neuro kabur secara terperinci. Topik-topik dibahagikan kepada 5 unit.

Setiap topik lengkap dengan gambar rajah, persamaan dan bentuk-bentuk perwakilan grafik untuk pembelajaran yang lebih baik dan pemahaman yang cepat. App akan menyediakan pembelajaran lebih cepat dan semakan cepat mengenai subjek ini.

mata pelajaran tambahan beberapa yang telah dimasukkan ke dalam aplikasi ini adalah

automata

Rangkaian neural sistem kabur

Sistem masa nyata

Beberapa topik yang dilindungi dalam permohonan ini adalah:

1. ujian Turing

2. Pengenalan kepada Kepintaran Buatan

3. Sejarah AI

Kitaran 4. AI

5. Representasi Pengetahuan

6. masalah AI biasa

7. Had AI

8. Pengenalan kepada Agents

9. Prestasi Agent

10. Agen pintar

11. Struktur Agen pintar

12. Jenis-jenis program ejen

13. Agents Goal berdasarkan

14. ejen berdasarkan Utility-

15. Agents and persekitaran

16. seni bina Agent

17. Cari Solutions

18. Spaces Negeri

19. Graph Mencari

20. A Generic Mencari Algoritma

21. Strategi Search yang tidak mengerti

22. Keluasan-First Search

23. heuristik Carian

24. AA ¢ Ë † â € "Search

25. Cari Tree

26. Kedalaman Cari pertama

27. Sifat Kedalaman Pertama Cari Cari

28. Bi-arah carian

29. Cari Graf

30. Strategi Cari Dimaklumkan

31. Kaedah Bermaklumat Carian

32. tamak Carian

33. Bukti Kebolehterimaan A *

34. Sifat Heuristik

35. lelaran-Pendalaman A *

36. Lain-lain Memory carian heuristik terhad

37. N-Queens eample

38. Pertentangan Carian

39. Algoritma Genetik

40. Permainan

41. keputusan Optimal dalam Permainan

algoritma 42. MINIMAX

43. Alpha Beta Pemangkasan

44. memundurkan

45. Teknik Consistency Didorong

46. ​​Path Ketekalan (K-Consistency)

47. Perhatikan

48. usulan Logik

49. Syntax of Calculus usulan

50. Representasi Pengetahuan dan penalaran

51. usulan Logik Inference

52. Fasal Definite usulan

53. Ilmu-Level Debugging

54. Peraturan Inference

55. Kekukuhan dan Kesempurnaan

56. First Order Logik

57. Penyatuan 58. Semantics

59. Herbrand Universe

60. Soundness, Kesempurnaan, Consistency, Satisfiability

61. Resolusi

62. Herbrand Revisited

63. Bukti tentang Search

64. Sesetengah Strategi Bukti

65. Bukan monotonic Penaakulan

66. Kebenaran Maintenance Systems

67. Sistem Peraturan Berdasarkan

68. Pure Prolog

69. Forward chaining

70. Chaining ke belakang

71. Pilihan antara ke hadapan dan ke belakang chaining

72. DAN / ATAU Trees

73. Hidden Markov Model

74. rangkaian Bayesian

75. Isu-isu Pembelajaran

76. Pembelajaran terselia

77. Pokok Keputusan

78. Pengetahuan Formalisms Perwakilan

79. Rangkaian Semantik

80 Inference dalam Net Semantic

81. Melanjutkan Nets Semantik

82 Frames

83 Slots sebagai Objek

84 bingkai Mentafsir

85 Pengenalan kepada Perancangan

86. Penyelesaian Masalah vs Perancangan

87. Logik Perancangan Berdasarkan

88. Perancangan Sistem

89. Perancangan seperti Search

90. Situasi-Space Planning Algoritma

Perancangan 91. separa Tempahan

92. Plan-Space Planning Algoritma

93. interleaving vs Non-interleaving daripada langkah Sub-Plan

94. Mudah Sock / Contoh Kasut

95. Pertimbangan berkebarangkalian

96. Kajian Teori Kebarangkalian

97. Semantics of Bayesian Networks

98. Pengenalan kepada Pembelajaran

99. Taksonomi Pengajian Systems

100. penggubalan Matematik masalah pembelajaran induktif

AI akan menjadi salah satu daripada teknologi yang paling penting pada zaman akan datang. Ia adalah satu kajian mesti mempunyai untuk kejuruteraan, sains komputer, kejuruteraan perisian dan lain-lain pelajar sains kognitif. Ia juga akan menjadi sangat penting bagi mekanikal, Automotive & elektrik pelajar kejuruteraan dan Profesional.

Memuat turun aplikasi untuk pengenalan kepada AI dan teknologi yang berkaitan.