Princess Nora University Artificial Intelligence

1. Princess Nora UniversityArtificial Intelligence CS 461 Level 8

2. Chapter 1: Introduction Included Topics : • What is AI ? • History of AI. • Applied Areas of AI. • What’s involved in Intelligence?

3. Recommended Books: • “Artificial Intelligence: A modern approach” Stuart Russell, Peter Norvig, Prentice Hall, 2003 (new edition 2006) 2. “Artificial Intelligence In Perspective”, by Daniel G. Bobrow. 3. Artificial Intelligence :A Guide to Intelligent Systems , MICHAEL NEGNEVITSKY, 2nd Edition.

4. What is AI ? (1) • "The exciting new effort to make computers think . . . machines with minds, in the full and literal sense" (Haugeland, 1985) • "[The automation of] activities that we associate with human thinking, activities such as decision-making, problem solving, learning .."(Bellman, 1978)

5. What is AI ? (2) • "A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes" (Schalkoff, 1 990) • "The branch of computer science that is concerned with the automation of intelligent behavior" (Luger and Stubblefield, 1993)

6. What is AI ? (3) Artificial Intelligence : is a science that has defined its goal as making machines do things that would require intelligence if done by humans. Intelligence: is ability to learn and understand to solve problems and to make decisions. A machine is thought intelligent if it can achieve human level performance in some cognitive task.

7. What is AI ? (4) Views of AI fall into four categories:

8. Thinking humanly (1) The way in which the computer carries out the tasks is important. • Cognitive Science → theories that study the way human would think . The interdisciplinary field of cognitive science brings together computer models from AI and experimental techniques from psychology to try to construct precise and testable theories of the workings of the human mind.

9. Thinking humanly (2) • Cognitive Science approach • Try to get “inside” our minds • E.g., conduct experiments with people to try to “reverse-engineer” how we reason, learning, remember, predict • Problems • Humans don’t behave rationally . e.g., insurance • The reverse engineering is very hard to do • The brain’s hardware is very different to a computer program

10. Acting Humanly: The Turing Test (1) Turing (1950) was interested in the following question: Can machines think? But he immediately decides that answering this question directly is hopeless. The Element of the Turing Test Are : • An interrogator (a person who will ask questions) • a computer (intelligent machine !!) • A person who will answer to questions • A curtain (separator)

11. Acting Humanly: The Turing Test (2) • Typed input/output only • Any kind of question is fair. • The player poses questions to the computer /other human. • Can the player reliably distinguish the computer from the human?

12. Acting Humanly: The Turing Test (3) • Suggested major components of AI: knowledge, reasoning, language understanding, learning • The computer would need to possess some capabilities: • Natural language processing: To communicate successfully. • Knowledge representation: To store what it knows or hears. • Automated reasoning: to answer questions and draw conclusions using stored information. • Machine learning: To adapt to new circumstances and to detect and extrapolate patterns. • Computer vision: To perceive objects. • Robotics :to manipulate objects and move.

13. Passing The Turing Test • A computer passes the Turing test if interrogators can not distinguish the machine from human on the basis of the answers to their questions.

14. Thinking rationally: "laws of thought" • Represent facts about the world via logic. • Use logical inference as a basis for reasoning about these facts. • Can be a very useful approach to AI • E.g., theorem-provers Limitations • Not all intelligent behavior is mediated by logical deliberation. • What is the purpose of thinking? What thoughts should I have?

15. Acting rationally : rational agent approach(1) Rational behavior: doing the right thing. The right thing: that which is expected to maximize goal achievement, given the available information.

16. Acting rationally : rational agent approach(2) • Advantages: - More general than the “laws of thought” approach. - More amenable to scientific development than human-based approaches.

17. A Brief History of AI (1) • 1943: early beginnings • McCulloch & Pitts: Boolean circuit model of brain • 1950: Turing • Turing's "Computing Machinery and Intelligence“ • 1956: birth of AI • Dartmouth meeting: "Artificial Intelligence“ name adopted • 1950s: initial promise • Early AI programs, including • Samuel's checkers program • Newell & Simon's Logic Theorist • 1955-65: “great enthusiasm” • Newell and Simon: GPS, general problem solver • Gelertner: Geometry Theorem Prover • McCarthy: invention of LISP

18. A brief History of AI (2) • 1966—73: Reality dawns • Realization that many AI problems are intractable • Limitations of existing neural network methods identified • Neural network research almost disappears • 1969—85: Adding domain knowledge • Development of knowledge-based systems • Success of rule-based expert systems, • E.g., DENDRAL, MYCIN • But were brittle and did not scale well in practice • 1986-- Rise of machine learning • Neural networks return to popularity • Major advances in machine learning algorithms and applications • 1990-- Role of uncertainty • Bayesian networks as a knowledge representation framework • 1995-- AI as Science • Integration of learning, reasoning, knowledge representation • AI methods used in vision, language, data mining, etc

19. Applied Areas of AI • Game playing • Speech and language processing • Expert reasoning • Planning and scheduling • Vision • Robotics

20. Playing chess Driving on the highway Translating languages Recognizing speech Diagnosing diseases Some Examples

21. Playing Chess • Environment? • Board • Actions? • Legal moves • Doing the right thing? • Moves that lead to wins

22. Recognizing Speech • Environment • Audio signal • Knowledge of user • Actions • Choosing word sequences • Doing the right thing • Recovering the users words

23. Diagnosing Diseases • Environment • Patient information • Results of tests • Actions • Choosing diseases • Choosing treatments • Doing the right thing • Eliminating disease

24. Translation • Environment • Source text to be translated • Actions • Word sequences in target language • Doing the right thing? • Words that achieve the same effect • Words that are faithful to the source

25. Driving • Environment • Restricted access highway • Actions • Accelerate, turn, navigate, other controls • Doing the right thing • Stay safe, get where you want to go, get there quickly

26. What’s involved in Intelligence? • Ability to interact with the real world • to perceive, understand, and act • e.g., speech recognition and understanding and synthesis • e.g., image understanding • e.g., ability to take actions, have an effect • Reasoning and Planning • modeling the external world, given input • solving new problems, planning, and making decisions • ability to deal with unexpected problems, uncertainties • Learning and Adaptation • we are continuously learning and adapting • our internal models are always being “updated” • e.g., a baby learning to categorize and recognize animals

27. H.W • Write about disillusion of AI in 1970 s ? • What We mean by reverse engineering? • Give two challenges of AI applications? • What is LISP ?