# Artificial Intelligence II - PowerPoint PPT Presentation

Artificial Intelligence II

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Artificial Intelligence II

## 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