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Artificial Intelligence II

Artificial Intelligence II Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication Engineering National Taiwan University Production System Common characteristics of reasoning problems Major components A collection of states A collection of productions

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Artificial Intelligence II

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Presentation Transcript

  1. Artificial Intelligence II Shyh-Kang Jeng Department of Electrical Engineering/ Graduate Institute of Communication Engineering National Taiwan University

  2. Production System • Common characteristics of reasoning problems • Major components • A collection of states • A collection of productions • A control system

  3. Portion of the 8-Puzzle’s State Graph

  4. Applications of Production System Framework • Playing games of chess • Drawing logical conclusions from given facts

  5. Deductive Reasoning

  6. Search Trees • Control system • Searches the state graph to find a path from the start node to the goal • A strategy is to build a search tree • Root: start state • Children: states reachable by applying one production • Walking up the tree from the goal

  7. An unsolved 8-Puzzle

  8. A Sample Search Tree

  9. Productions Stack Top of stack Move the 5 tile down Move the 3 tile right Move the 2 tile up Move the 5 tile left Move the 6 tile up

  10. Tree-Searching Strategies • Breadth-first search • Depth-first search • Heuristics • A quantitative measure to determine which state is closest to the goal

  11. An Unsolved 8-Puzzle Heuristics: 7 (sum of distances)

  12. A Heuristic Algorithm

  13. Beginning of a Heuristic Search

  14. Search Tree After Two Passes

  15. Search Tree After Three Passes

  16. Complete Search Tree

  17. A Neuron in a Living Biological System

  18. Processing Unit

  19. Representation of a Processing Unit

  20. A Neural Network with Two Different Programs

  21. A Neural Network with Two Different Programs

  22. Uppercase C and Uppercase T

  23. Various Orientations of C and T

  24. Character Recognition System

  25. Letter C in the Field of View

  26. The Letter T in the Field of View

  27. Desired Output Actual Output Inputs Adjusting Weights Using Error Back Propagation Network

  28. Genetic Algorithms • Apply our knowledge of natural evolution to problem-solving • Algorithm • Represent potential solutions as strings of symbols • A collection of potential solutions is generated and tested • The better examples from the collection are crossed to form a new generation of potential solutions

  29. Poker Strategies

  30. Configuration of an Artificial Neural Network

  31. Coding Artificial Neural Networks

  32. Applications of Artificial Intelligence • Language processing • Robotics • Database systems • Expert systems

  33. A Semantic Net

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