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CSE 471/598 Introduction to Artificial Intelligence. http://www.public.asu.edu/~huanliu/AI04S/cse471-598.htm. Spring 2004. Introduction. You, TA: Srihari Venkatesan, Brickyard ? TBA soon, gvs@asu.edu, and me hliu@asu.edu (http://www.public.asu.edu/~huanliu). The course.
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CSE 471/598 Introduction to Artificial Intelligence http://www.public.asu.edu/~huanliu/AI04S/cse471-598.htm Spring 2004
Introduction • You, • TA: Srihari Venkatesan, Brickyard ? TBA soon, gvs@asu.edu, and • me hliu@asu.edu (http://www.public.asu.edu/~huanliu) CSE 471/598, H. Liu
The course • What is AI (many definitions of AI) • One definition: a field to enable computers with human-level intelligence with attempts to understand intelligent entities. • What is this course about • understand ourselves better • build automated intelligent agents • improve problem solving skills CSE 471/598, H. Liu
The course (2) • Projects (30%, 2*15%) – all in Lisp • Exam(s) (2*25%) • Homework (~20%) • Quizzes and class participation (~10%) • Late penalty, YES. • Academic integrity (http://www.public.asu.edu/~huanliu/conduct.html) CSE 471/598, H. Liu
Plan • Text Book: AI - A Modern Approach • Reading assignment: chapters covered • 15 weeks - about 13-15 chapters • One major subject per week TIP Try to keep up and avoid catch-up CSE 471/598, H. Liu
Plan (2) • Major topics • Intelligent agents • Problem solving • Knowledge and reasoning • Acting logically • Learning • Uncertainty TIP Comprehend the topics with your common sense CSE 471/598, H. Liu
Welcome to this class! • We will work together throughout this semester. • Questions and suggestions are most welcome. CSE 471/598, H. Liu
Introduction of AI and LISP - Gearing up for a fun semester about intelligent agents
What is AI (2) • Acting humanly: The Turing test (1950) • What do we need to pass the test • Thinking humanly: Cognitive modeling • “Think-aloud” to learn from human and recreate in computer programs (GPS) • Thinking rationally: Syllogisms, Logic • Acting rationally: A rational agent CSE 471/598, H. Liu
Foundations of AI • Philosophy (428 B.C. - Present) – reasoning and learning • Can formal rules be used to draw valid conclusions? • How does the mental imind arise from a physical brain? • Where does knowledge come from? • How does knowledge lead to action? CSE 471/598, H. Liu
Mathematics (c. 800 - Present) - logic, probability, decision making, computation • What are the formal rules to draw conclusions? • What can be computed? • How do we reason with uncertain information? • Economics (1776-present) • How should we make decisions so as to maximize payoff? • How should we do this when others may not go along? • How should we do this when the payoff may be far in the future? CSE 471/598, H. Liu
Neuroscience (1861-present) • How do brains process information • Psychology (1879 - Present) - investigating human mind • How do humans and animals think and act? • Computer engineering (1940 - Present) - ever improving tools • How can we build an efficient computer? CSE 471/598, H. Liu
Control theory and Cybernetics (1948-present) • How can artifacts operate under their own control? • Linguistics (1957 - Present) - the structure and meaning of language • How does language relate to thought? CSE 471/598, H. Liu
Brief History of AI • Gestation of AI (1943 -1955) • McCulloch and Pitts’s model of artificial neurons • Minsky’s 40-neuron network • Birth of AI (1956) • A 2-month Dartmouth workshop of 10 attendees – the name of AI • Newell and Simon’ Logic Theorist • Early enthusiasm, great expectations (1952 - 1969) • GPS by Newell and Simon, Lisp by McCarthy, Blockworld by Minsky CSE 471/598, H. Liu
AI facing reality (1966 - 1973) • Many predictions of AI coming successes • A computer would be a chess champion in 10 years (1957) • Machine translation – Syntax is not enough • Intractability of the problems attempted by AI • Knowledge-based systems (1969 - 1979) • Knowledge is power, acquiring knowledge from experts • Expert systems (MYCIN) • AI - an industry (1980 - present) • Many AI systems help companies to save money and increase productivity CSE 471/598, H. Liu
The return of neural networks (1986 – present) • PDP books by Rumelhart and McClelland • Connectionist models vs. symbolic models • AI – a science (1987 – present) • Build on existing theories vs. propose brand new ones • Rigorous empirical experiments • Learn from data – data mining • AI – intelligent agents (1995 – present) • Working agents embedded in real environments with continuous sensory inputs CSE 471/598, H. Liu
Smart bombs Deep Blue, and others E-Game industry Intelligent houses Intelligent appliances RoboCup Biometrics Communications (email, word processor) Auto driving from E to W (98% vs. 2%) Consumer protection Some examples of AI applications CSE 471/598, H. Liu
Refresher for LISP • What is it? • ANSI Common Lisp, Paul Graham, Prentice Hall • Input (e.g., terminal, files) • Output (e.g., files, printing) • Processing (various operations) • How to run it? CSE 471/598, H. Liu