CSE 471/598,CBS598 Introduction to Artificial Intelligence Spring

CSE 471/598, CBS 598 H. Liu2 Introduction You, TA: Surendra Singhi, Brickyard 214 MW 12:15-1:15 (venue and time are tentative), and Me: ( Slides are updated periodically based on feedback

CSE 471/598, CBS 598 H. Liu3 Course introduction 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 (multi-purpose) understand ourselves better build automated intelligent agents improve problem solving skills

CSE 471/598, CBS 598 H. Liu4 Course workload and evaluation A lot of work is expected from you! If you are not ready, please reconsider  Projects (30%, 2*15%) – all in Lisp?  Exam(s) (2*25%)  Homework (~20%)  Quizzes and class participation (~10%) Late penalty, YES and exponentially increased Academic integrity (

CSE 471/598, CBS 598 H. Liu5 Course plan Text Book: AI - A Modern Approach 2 nd Edition in green Reading assignment: chapters covered 15 weeks - about chapters Our goal: “to finish all chapters” One major subject per week TIP Try to keep up and avoid catch-up

CSE 471/598, CBS 598 H. Liu6 Major Topics Intelligent agents Problem solving Knowledge and reasoning Acting logically Learning Uncertainty TIP Comprehend the topics with your common sense

CSE 471/598, CBS 598 H. Liu7 Welcome to this class! We will work together throughout this semester. Questions and suggestions are welcome anytime. E.g., if you find anything incorrect or unclear, also send it to me. You get feedback from us, and I need feedback from you, too Use myASU to send and for discussions

Introduction of AI - Gearing up for a fun semester about intelligent agents

CSE 471/598, CBS 598 H. Liu9 What is AI (2) About thinking and acting We are not alone, but … (Homo genus) 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)  What the Eyes see, a camera cannot Thinking rationally: Syllogisms, Logic Acting rationally: A rational agent to achieve best or best expected outcomes

CSE 471/598, CBS 598 H. Liu10 Foundations of AI Philosophy (428 B.C. - Present) – reasoning and learning Can formal rules be used to draw valid conclusions? How does the mental mind arise from a physical brain? Where does knowledge come from? How does knowledge lead to action?

CSE 471/598, CBS 598 H. Liu11 Mathematics (c 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, CBS 598 H. Liu12 Neuroscience (1861-present) How do brains process information  Processing speed, memory size in a computer (Figure 1.3) Psychology ( Present) - investigating human mind How do humans and animals think and act?  Mind Wide Open Computer engineering ( Present) - ever improving tools How can we build an efficient computer?  Moors Law

CSE 471/598, CBS 598 H. Liu13 Control theory and Cybernetics (1948- present) How can artifacts operate under their own control? Feedback Linguistics ( Present) - the structure and meaning of language How does language relate to thought? Computational linguistics

CSE 471/598, CBS 598 H. Liu14 Brief History of AI Gestation of AI ( ) McCulloch and Pitts’s model of artificial neurons Minsky’s 40-neuron network Alan Turing’s Computing Machinary and Intelligence Birth of AI (1956) A 2-month Dartmouth workshop of 10 attendees – the name of AI Newell and Simon’ Logic Theorist Should another name like `computational rationality’ be used? Early enthusiasm, great expectations ( ) GPS by Newell and Simon, Lisp by McCarthy, Blockworld by Minsky

CSE 471/598, CBS 598 H. Liu15 AI facing reality ( ) 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 “What computers cannot do” in 76 Knowledge-based systems ( ) Knowledge is power, acquiring knowledge from experts Expert systems (MYCIN) AI - an industry ( present) Many AI systems help companies to save money and increase productivity

CSE 471/598, CBS 598 H. Liu16 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, CBS 598 H. Liu17 Some examples of AI applications Smart bombs Deep Blue, and others E-Game industry Intelligent houses Intelligent appliances RoboCup Biometrics Communications ( , word processor) Auto driving from E to W (98% vs. 2%) Consumer protection

CSE 471/598, CBS 598 H. Liu18 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?