Complete free handbook of Artificial Intelligence, Learn a topic in a minute
About Artificial Intelligence : AI
Artificial Intelligence : AI is an education app developed by Engineering Wale Baba.
Download Statistics
Artificial Intelligence : AI has been downloaded 100 thousand times. In the last 30 days, the app was downloaded 790 times.
User Ratings
Artificial Intelligence : AI is rated 4.00 out of 5 stars. The rating is based on 1.5 thousand ratings.
App Information
Artificial Intelligence : AI is FREE to download. The APK download size is 12.49 MB. The latest version available is 18.0. The last update was on March 14, 2026.
Technical Requirements
Artificial Intelligence : AI requires Android 4.1+ or higher. The app has a content rating of Everyone. The app has been available on Google Play October 2015.
Description
Artificial Intelligence (AI) :
It is a pocket Engineering Book and wherever you can read this. In this book cover most of topics and explain with figure, tables etc..
It covers more than 600 topics of Artificial Intelligence, Automata, Real-time systems & Neuro fuzzy in detail. The topics are divided into 5 units.
It is field of study on creating computer & software capable of intelligent behavior.
The App is a Handbook for easy understanding the Artificial Intelligence (AI). It covers 142 around topics of Artificial Intelligence in detail.
The AI field is interdisciplinary, in which a number of sciences and professions converge, including computer science, mathematics, psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.
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. Mathematical formulation of the inductive learning problem 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
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