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Artificial Intelligence - I

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    Artificial Intelligence - I

    by: faadooengineers.com 9 6.4

    6.4 Users
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    DOWNLOAD  $1.00


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    This ultimate 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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    Users review

    from 9 reviews

    "Good"

    6.4