1. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 11: Artificial Intelligence Computer Science: An Overview Tenth Edition by J. Glenn Brookshear Modified by Senem Kumova Metin

2. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-2 Chapter 11: Artificial Intelligence 11.1 Intelligence and Machines 11.2 Perception (Understanding Image, Speech or WrittenText ) 11.3 Reasoning

3. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-3 Intelligent Agents Agent: A “device” that responds to stimuli from its environment –Sensors –Actuators (e.g. wheels,legs, speech sythesizers) Much of the research in artificial intelligence can be viewed in the context of building agents that behave intelligently

4. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-4 Levels of Intelligent Behavior Reflex: predetermined responses to the input data More intelligent behavior requires knowledge of the environment and involves such activities as: –Goal seeking (e.g Winning a game of chess) –Learning (developing procedural knowledge or storing declarative knowledge)

5. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-5 Figure 11.1 The eight-puzzle in its solved configuration

6. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-6 Figure 11.2 Our puzzle-solving machine (The agent)

7. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-7 Approaches to Research in Artificial Intelligence Engineering track (develop systems that exhibit intelligent behaviour) –Performance oriented Theoretical track (develop a computational understanding of human behaviour) –Simulation oriented

8. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-8 Turing Test Test setup: Human interrogator communicates with test subject by typewriter. Test: Can the human interrogator distinguish whether the test subject is human or machine?

9. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-9 Techniques for Understanding Images Template matching Image processing (identifying characteristics of images) –edge enhancement –region finding –smoothing, Image analysis (understanding what these characterictics mean)

10. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Image processing –Edge enhancement : Applying techniques to fclarify boundaries between regions –Region finding : Find areas which have common properties –Smoothing: Removing flaws in the image 11-10

11. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Smoothing 11-11

12. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-12 Language Processing Syntactic Analysis (e.g. Parsing, Tokenization) Mary gave a card  Subject verb object Semantic Analysis -> Find grammatical role of each word Mary gave John a card = John got a card from Mary Contextual Analysis (understanding process) “Kitapları taşırken kolum koptu”

13. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Language Processing Information retrieval : Identify the documents related to the topic at hand Information extraction: Extracting information from documents so that it takes a form that is useful in other applications --Answers of questions are stored as forms 11-13

14. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-14 Figure 11.3 A semantic net (A type of form which information extractor record information)

15. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-15 REASONING: Components of a Production Systems 1. Collection of states –Start (or initial) state –Goal state (or states) 2. Collection of productions(rules or moves) –Production: an operation that can be performed in the applcation environment to move from one state to another –Each production may have preconditions 3. Control system: decides which production to apply next (it includes the problem space)

16. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-16 Reasoning by Searching State Graph: All states and productions Search Tree: A record of state transitions explored while searching for a goal state –Breadth-first search –Depth-first search

17. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-17 Figure 11.4 A small portion of the eight-puzzle’s state graph

18. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-18 Figure 11.5 Deductive reasoning in the context of a production system (Inference rules)

19. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-19 Figure 11.6 An unsolved eight-puzzle

20. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-20 Figure 11.7 A sample search tree

21. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-21 Figure 11.8 Productions stacked for later execution

22. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-22 Heuristic Strategies Developing a full search tree is impratical in some cases, as a result instead of building the tree in a breath first manner, build it using depth first method. Identify which of several steps to be the most promising Heuristic: A “rule of thumb” for making decisions

23. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-23 Heuristic Strategies Heuristic: A “rule of thumb” for making decisions Requirements for good heuristics –Must be easier to compute than a complete solution –Must provide a reasonable estimate of proximity to a goal

24. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-24 Figure 11.9 An unsolved eight-puzzle

25. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-25 Figure 11.10 An algorithm for a control system using heuristics

26. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-26 Figure 11.11 The beginnings of our heuristic search

27. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-27 Figure 11.12 The search tree after two passes

28. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-28 Figure 11.13 The search tree after three passes

29. Copyright © 2008 Pearson Education, Inc. Publishing as Pearson Addison-Wesley 11-29 Figure 11.14 The complete search tree formed by our heuristic system