IS-341 INTRODUCTION TO ARTIFICIAL INTELLIGENCE

1. IS-341INTRODUCTION TO ARTIFICIAL INTELLIGENCE Semester II (2010-11) Introduction: Chapter 1

2. IS- 341 • Homepage: http://sites.google.com/site/pnuis341/ • Visit the web page for schedule, lecture notes, tutorials, assignment, grading, office hours, etc. Textbook: S. Russell and P. NorvigArtificial Intelligence: A Modern Approach Prentice Hall, 2003, Second Edition

3. Outline • Course overview • What is AI? • A brief history • What AI can do today ?

4. Intelligence? • What do you believe what intelligence is? • Is it intelligent to think like a human? • Is it intelligent to act like a human? • Is “human” equivalent to “intelligent”? Intelligence = Knowledge + feel, understand, process, communicate, judge, and learn Characteristics of Intelligence • ‰ Ability to Communicate • ‰ Internal Knowledge • ‰ Ability to Learn • ‰ Self Awareness

5. Artificial Intelligence Tasks • Problem Solving • Find a solution to a given problem • Find the shortest route from KFUPM to PNU • Assign pilots to flights so that costs are minimized • Devise a plan to get an A+ in IS 341 • Reasoning • Express your knowledge and derive hypotheses • Proof mathematical theorems • Make “justifiable” decisions in uncertain environments

6. Artificial Intelligence Tasks • Learning • Adjust an internal representation so that it is in accordance with observations made • Revise Newton’s idea of space and time after observing that light travels at a constant speed • Interaction • Communicate • Understand spoken language • Perceive • Look at a photo an identify Trinity • Act

7. AI in Action !! Applications of AI

8. Acting humanly: Turing Test • Turing (1950) "Computing machinery and intelligence": • "Can machines think?"  "Can machines behave intelligently?" • Operational test for intelligent behavior: the Imitation Game • Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes • Anticipated all major arguments against AI in following 50 years • Suggested major components of AI: knowledge, reasoning, language understanding, learning

9. AI prehistory • Philosophy Logic, methods of reasoning, mind as physical system foundations of learning, language, rationality • Mathematics Formal representation and proof algorithms, computation, (un)decidability, (in)tractability, probability • Economics utility, decision theory • Psychology phenomena of perception and motor control, experimental techniques • Computer building fast computers engineering • Control theory design systems that maximize an objective function over time

10. Abridged history of AI • 1943 McCulloch & Pitts: Boolean circuit model of brain • 1950 Turing's "Computing Machinery and Intelligence" • 1956Dartmouth meeting: "Artificial Intelligence" adopted • 1952—69 Look, Ma, no hands! • 1950s Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine • 1965 Robinson's complete algorithm for logical reasoning • 1966—73 AI discovers computational complexity Neural network research almost disappears • 1969—79 Early development of knowledge-based systems • 1980-- AI becomes an industry • 1986-- Neural networks return to popularity • 1987-- AI becomes a science • 1995-- The emergence of intelligent agents

11. What AI Systems can do today? • Planning: • DARPA's DART system used in Desert Storm and Desert Shield operations to plan logistics of people and supplies. • European space agency planning and scheduling of spacecraft assembly, integration and verification. • Speech Recognition: • Computer Vision: • Face recognition programs in use by banks, government, etc. • Handwriting recognition.

12. What AI Systems can do today? • Game Playing: • Computer programs beat world’s best players in chess e.g Deep Blue by IBM • Playing “Jeopardy” – question answering