1. 1 CS 2710, ISSP 2610 Foundations of Artificial Intelligence introduction

2. 2 Outline Course information and syllabus Introduction to AI

3. 3 4 Views of AI “The automation of activities that we associate with human thinking…” Bellman 1978 “The study of mental faculties through the use of computational models” Charniak&McDermott “The art of creating machines that perform functions that require intelligence when performed by people.” (Kurzweil, 1990) “The branch of CS that is concerned with the automation of intelligent behavior.” Lugar&Stubblefield

4. 4 Basic Framework Getting computers to do the right thing based on their circumstances and what they know.

5. 5 Applied Areas of AI Game playing Speech and language processing Expert reasoning and theorem proving Planning and scheduling Vision Robotics

6. 6 Some Examples Playing chess Driving on the highway Mowing the lawn Answering questions Recognizing speech Diagnosing diseases Translating languages

7. 7 AI is a synergy among… Philosophy: Can a machine think? What are knowledge and belief? Logic and reasoning… psychology and cognitive science: problem solving skills… Linguistics: syntax, semantics, pragmatics…

8. 8 Synergy Among… Computer science and engineering: complexity theory, algorithms, logic and inference, programming languages, system building,… Mathematics, physics: statistical modeling, complex systems, chaos, game theory,… Economics: decision theory,… Neurobiology: how does the brain process information?...

9. 9 What’s involved in intelligence? Ability to interact with the real world –Perceive, understand, and act Reasoning and planning –Modeling external world –Problem solving, planning, decision making Learning and adaptation

10. 10 Goals in AI Engineering goal: solve real-world problems. Build systems that exhibit intelligent behavior Scientific goal: To understand what kinds of computational mechanisms and knowledge are needed for modeling intelligent behavior

11. 11 Turing Test (1950) Interrogator asks questions of two agents who are out of sight and hearing. One is person the other is a computer. If the interrogator can’t reliably distinguish between human and computer, then the computer is deemed “intelligent”

12. 12 Eliza (Joseph Weizenbaum in the last 60s) Takes the role of a psychoanalyst in a psychiatric interview. Sample dialog and modern Turning testSample dialog and modern Turning test

13. 13 Turing Test Pros: Objective evaluation. Focus on behavior (how could we evaluate whether a computer thinks like a human?) Cons: as much a test of the judge as it is of the machine; promotes development of artificial con artists (Newel and Simon 1976). But….

14. 14 Passing the Test Free conversation is very hard But people are prone towards attributing human qualities to technology

15. 15 Implications Whether or not we set out to build intelligent interactive agents, people expect computers to act like people

16. 16 Challenges Ahead Systems lack generality and adaptability They can’t easily switch contexts Key problems: knowledge acquisition, lack of commonsense knowledge, lack of sufficient data, what aspects of context are relevant?

17. 17 Example Information extraction example: consider brittleness and what we could do about itInformation extraction example:

18. 18 In-Class Discussion Questions This file