1. Can Machines Think? Rob Kremer Department of Computer Science University of Calgary

2. 22 Intelligence What is intelligence??? g

3. 33 Intelligence n Turing Test: A human communicates with a computer via a teletype. If the human can’t tell he is talking to a computer or another human, it passes. ? g

4. 44 Intelligence n Add vision and robotics to get the total Turing test. g

5. 55 Weak and Strong AI Claims n Weak AI: –Machines can be made to act as if they were intelligent n Weak AI: –Machines can be made to act as if they were intelligent Strong AI: –Machines that act intelligently have real, conscious minds. Strong AI: –Machines that act intelligently have real, conscious minds. g

6. 66 What is Intelligence? n The Chinese Room g

7. 77 What is Intelligence? n Replacing the brain g

8. 88 What is AI? g

9. 99 How do we classify research as AI? g

10. 10 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

11. 11 Learning n Explanation –Discovery –Data Mining n No Explanation –Neural Nets –Case Based Reasoning g

12. 12 Learning: Explanation n Cases to rules g

13. 13 Learning: No Explanation n Neural nets Doctor, doctor, I have a runny nose! You’re going to die. *ULP*! Why do you say that??? No idea. The Neural Net said so. g

14. 14 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

15. 15 Rule-Based Systems n Logic Languages –Prolog, Lisp n Knowledge bases n Inference engines g

16. 16 Rule-Based Languages: Prolog Father(abraham, isaac).Male(isaac). Father(haran, lot).Male(lot). Father(haran, milcah).Female(milcah). Father(haran, yiscah).Female(yiscah). Son(X,Y) ← Father(Y,X), Male(X). Daughter(X,Y) ← Father(Y,X), Female(X). Son(lot, haran)? X g

17. 17 Rule Based Systems n KRS

18. 18 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

19. 19 Search n “All AI is search” –Game theory –Problem spaces n Every problem is a “virtual” tree of all possible (successful or unsuccessful) solutions. n The trick is to find an efficient search strategy.

20. 20 Search: Games 9!+1 = 3 62,880 nodes g

21. 21 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

22. 22 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

23. 23 Ability-Based Areas n Computer vision n Natural language recognition n Natural language generation n Speech recognition n Speech generation n Robotics g

24. 24 Natural Language: Translation “The spirit is strong, but the flesh is weak.” → Translate to Russian “Дух сильн, но плоть слаба.” ← Translate back to English “The vodka is great, but the meat is rancid!” g

25. 25 Natural Language Recognition g

26. 26 Natural Language Representation “Tom believes Mary wants to marry a sailor.” g

27. 27 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents RoboCup ChallengeRoboCup Game g

28. 28 Approaches to AI n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents n Learning n Rule-Based Systems n Search n Planning n Ability-Based Areas n Robotics n Agents g

29. 29 Agent Communication Alice Bob (performative: request, content: attend(Bob,x)) Can you attend this meeting? (performative: agree, content: attend(Bob,x)) Sure... (performative: inform, content: attend(Bob,x)) I’m here (performative: confirm, content: attend(Bob,x)) Thanks for coming. (performative: ack, content: attend(Bob,x)) (nod) (performative: ack, content: attend(Bob,x)) (nod) (performative: ack, content: attend(Bob,x)) (nod) gg

30. 30 Agent Communication reply-propose-discharge(Alice,Bob,x) act(Bob,Alice,x) propose-discharge(Bob,Alice,x) Alice Bob request inform reply agree informack propose-discharge done reply informack reply-propose-discharge confirm reply informack reply(Bob,Alice,x) ack(Bob,Alice,x) ack ack(Bob,Alice,x) ack ack(Alice,Bob,x) ack ack(Alice,Bob,x) ack g

31. 31 How far have we got? n Our best systems have the intelligence of a frog n Mind you, how many frogs spend all their intelligence controlling a nuclear power plant? g

32. 32 Happy Birthday, Shelby!

33. 33 g

34. 34 g