2. Game AI versus AI Héctor Muñoz-Avila

3. Game AI Do you know what is attack Kung-Fu style?

4. Half-Life: Gordon Freeman’s First Encounter with the Marines Do they attack Kung-Fu style?

5. Half-Life Kung-Fu Attack Actually no more than 2 marines are attacking at any time The other marines take cover, move around etc. When one of the attacking marines run out of ammo, is wounded, dies, etc., one of the others take his place Some reactions are hard-coded and scenario-dependent

6. Game AI Term refers to the algorithms controlling: –The computer-controlled units/opponents –Gaming conditions (e.g., weather) –Path finding Attack Kung-Fu style is an example of game AI for the computer opponent Programming intentional mistakes is also part of controlling the computer opponent “AI”

7. Programming “Good” AI Opponent (according to Lars Liden; Ch. 2) Move before firing Make mob/enemy visible (but the Alien vs. Predator does the opposite)

8. Programming “Good” AI Opponent (II) (according to Lars Liden; Ch. 2) Have horrible aim (rather than doing less damage) Miss the first time Warn the player (e.g., music, sound) Kung-Fu attacks

9. What is AI? Systems that think like humans Systems that think rationally Systems that act like humans Systems that act rationally Categories for definitions of AI

10. The Turing Test: Preliminaries Designed by Alan Turing (1950) The Turing test provides a satisfactory operational definition of AI It’s a behavioral test (i.e., test if a system acts like a human) Problem: it is difficult to make a mathematical analysis of it

11. The Turing Test The Turing Test: a computer is programmed well enough to have a conversation with an interrogator (for example through a computer terminal) and passes the test if the interrogator cannot discern if there is a computer or a human at the other end machine ??

12. The Turing Test vs. AI Fields For a program to pass the Turing Test, it needs to pass the exhibit the following capabilities: Natural language processing Knowledge representation Automated reasoning Machine learning

13. Loebner Prize Each year (since 1994) a competition is made to see if a computer passes the Turing Test The first program to pass it will receive 100k Controversial: Minsky offer 100 if anyone finish it Still, it is interesting to observe capabilities Machines seems to have come close to fulfill Turing’s prediction (5 minutes)

14. Loebner Prize (II) ENTRANT: Welcome judge 4 JUDGE: Hello. What's the weather outside? ENTRANT: I haven't been outside much today. I am fond of asparagus myself. JUDGE: How old are you? ENTRANT: I'm about 30. JUDGE: About? ENTRANT: I can talk about Star Trek. JUDGE: No let's talk about you. Exactly how old are you? ENTRANT: Right you are batman. Main drawbacks: Yes/No test No incremental goals …

15. Other Predictions from Turing Predicted that by the year 2000 a computer will have 30% chances to fool a person for 5 minutes Anticipated the major arguments against AI: The mathematical objection to AI Argument from Informality

16. The Mathematical Objection to AI The Halting Problem Can we write a program in a language L (i.e., java), that recognizes if any program written in that language ends with a given input? Answer: No (Turing, 1940’s: the set {(P,I) : P will stop with an input I} is not Turing-computable) Proof by contradiction (using a Universal Turing Machine - CSC318: Automata Theory-)

17. The Mathematical Objection to AI Argument against AI: a human can determine if a program ends or not Thus, computers machines are inferior as humans Argument against this argument:  If the brain is a deterministic device then it is a formal system like a computer is (though more complicated)  If the brain has some non deterministic aspects, then we can incorporate devices that has non deterministic behavior

18. Point of View in Our Course These discussions refer to pros and cons of constructing a machine that behaves like a human A wide range of techniques have been developed as a result of the interest in AI In practice, some of these techniques have been effectively used to enhance computer games Studying these successfully applied techniques for games and promising directions is the focus of our course We left the discussion of whether a Game exhibit a human- like behavior or not to cognitive scientist or philosophers

19. AI: Genesis Logical reasoning calculus was conceived (Leibniz, 17 century) Leibiz’ motivation: solve intellectual arguments by calculation Boolean logic (Boole, 1847) Predicate Logic (Frege, 1879): Begriffsschrift Incompleteness Theorem (Goedel, 1940’s)

20. AI: Some Historical Highlights Turing’s article about what machines can do Term AI is coined at the Dartmouth conference (1956) General Problem Solver (Newell & Simon; 1958) Period of great expectations

21. Early Stages, Great Expectations (what they thought they could achieve) Jenna: What were you just thinking? Data: In that particular moment, I was reconfiguring the warp field parameters, analyzing the collected works of Charles Dickens, calculating the maximum pressure I could safely apply to your lips, considering a new food supplement for Spot... Jenna: I'm glad I was in there somewhere. (from In Theory episode)

22. AI: Some Historical Highlights (cont’d) Perceptrons: limits to neural networks (Minksy and Papert; 1969) Knowledge-based systems (1970’s) AI becomes an industry. Early successes of Expert systems

23. AI: Some Historical Highlights (cont’d) It becomes clear that expert systems are hard to create (problem known as the Knowledge Acquisition bottle-neck) Renaissance of neural networks as connectionism 1990’s: more consolidated approaches to AI, more realistic expectations, fielded applications:  Applications of machine learning to data-mining  Applications of various AI techniques to computer games

24. Some Subareas of AI Search Planning Natural language processing Machine learning Case-based reasoning Robotics Computer vision Neural networks