CS3243 FOUNDATIONS OF ARTIFICIAL INTELLIGENCE
| AY2004/2005 Semester 2 | |
| Introduction: Chapter 1 |
| Course home page: http://www.comp.nus.edu.sg/~cs3243 | |
| IVLE for homework submission and forum communication. | |
| Textbook: S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, Second Edition | |
| Lecturer: Min-Yen Kan (S15 05-05) | |
| Grading: Programming assignments (20%, 20%), Midterm test (20%), Final exam (40%) | |
| Class participation can only revise your grade upwards | |
| Lecture and tutorial attendance is mandatory | |
| Midterm test (in class, 1 hr) and final exam (2 hrs) are both closed book |
| Course overview | |
| What is AI? | |
| A brief history | |
| The state of the art |
| Introduction and Agents (chapters 1, 2) | ||
| Search (chapters 3, 4, 5, 6) | ||
| Logic (chapters 7, 8, 9) | ||
| Uncertainty (chapters 13, 14) | ||
| Learning (chapters 18, 20) | ||
| Optional Lectures: | ||
| Natural Language Processing (chapters 22, 23) | ||
| Planning and Robotics (chapters 11, 12, 25) | ||
| Views of AI fall into four categories: | |
| Thinking humanly Thinking rationally | |
| Acting humanly Acting rationally | |
| The textbook advocates "acting rationally" |
| Turing (1950) "Computing machinery and intelligence": | |
| "Can machines think?" à "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 |
Thinking humanly: cognitive modeling
| 1960s "cognitive revolution": information-processing psychology | |||
| Requires scientific theories of internal activities of the brain | |||
| How to validate? Requires | |||
| 1) Predicting and testing behavior of human subjects (top-down) | |||
| or 2) Direct identification from neurological data (bottom-up) | |||
| Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from AI | |||
Thinking rationally: "laws of thought"
| Aristotle: what are correct arguments/thought processes? | ||
| Several Greek schools developed various forms of logic: notation and rules of derivation for thoughts; may or may not have proceeded to the idea of mechanization | ||
| Direct line through mathematics and philosophy to modern AI | ||
| Problems: | ||
| Not all intelligent behavior is mediated by logical deliberation | ||
| What is the purpose of thinking? What thoughts should I have? | ||
Acting rationally: rational agent
| Rational behavior: doing the right thing | |
| The right thing: that which is expected to maximize goal achievement, given the available information | |
| Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action |
| An agent is an entity that perceives and acts | ||
| This course is about designing rational agents | ||
| Abstractly, an agent is a function from percept histories to actions: | ||
| [f: P* à A] | ||
| For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance | ||
| Caveat: computational limitations make perfect rationality unachievable | ||
| à design best program for given machine resources | ||
| Philosophy Logic, methods of
reasoning, mind as physical system foundations of learning, language, rationality |
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| Mathematics Formal representation and
proof algorithms, computation, (un)decidability, (in)tractability, probability |
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| Economics utility, decision theory | |
| Neuroscience physical substrate for mental activity | |
| Psychology phenomena of perception
and motor control, experimental techniques |
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| Computer building fast computers
engineering |
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| Control theory design systems that
maximize an objective function over time |
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| Linguistics knowledge representation, grammar |
| 1943 McCulloch & Pitts: Boolean circuit model of brain | |
| 1950 Turing's "Computing Machinery and Intelligence" | |
| 1956 Dartmouth 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 |
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| 1965 Robinson's complete algorithm for logical reasoning | |
| 1966–73 AI discovers computational
complexity Neural network research almost disappears |
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| 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 |
| Deep Blue defeated the reigning world chess champion Garry Kasparov in 1997 | |
| Proved a mathematical conjecture (Robbins conjecture) unsolved for decades | |
| No hands across America (driving autonomously 98% of the time from Pittsburgh to San Diego) | |
| During the 1991 Gulf War, US forces deployed an AI logistics planning and scheduling program that involved up to 50,000 vehicles, cargo, and people | |
| NASA's on-board autonomous planning program controlled the scheduling of operations for a spacecraft | |
| Proverb solves crossword puzzles better than most humans |