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EE562 ARTIFICIAL INTELLIGENCE FOR ENGINEERS

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Presentation on theme: "EE562 ARTIFICIAL INTELLIGENCE FOR ENGINEERS"— Presentation transcript:

1 EE562 ARTIFICIAL INTELLIGENCE FOR ENGINEERS
University of Washington, Department of Electrical Engineering Spring 2005 Instructor: Professor Jeff A. Bilmes

2 EE562 General Introduction to AI for Engineers
what does “for Engineers” mean? We will emphasize practical aspects of AI techniques, and how to use them for real world problems and system building. Lecturer: Prof. Jeff A. Bilmes TA: Winyu Chinthammit Course home page: Bookmark this page for this quarter. Prerequisites: basic programming, algorithms and data structures, and basic logic and probability (or permission of instructor, if you are unsure ask me after class). Textbook: S. Russell and P. Norvig Artificial Intelligence: A Modern Approach Prentice Hall, 2003, Second Edition excellent text, the standard in the field. Homework: There will be 3-4 homeworks assigned for the quarter. They will be combination of standard work problems but will also involve significant programming assignments. They will be due roughly 2 weeks after assigned (but don’t start late!!) Exams: There will be both a midterm (May 2nd, 1.5 hours) and a Final (June 8th, 2 hours)

3 EE562 Reading This Week: AIMA: Chapters 1 and 2.
Grading: 33% homework, 33% midterm, and 33% final. S/NS: Must do all problem sets (need not do midterm/final). Class participation is also counted (attendance, asking and answering questions). Last day of class: June 1st, 2005 Holiday: May 30th, Veterans day. Final Exam: Wed, June 8th, 2:30-4:30. Reading This Week: AIMA: Chapters 1 and 2.

4 Course overview 10 weeks, 19 1.5 hour lectures.
Introduction and Agents (chapters 1,2) Search, CSP, Games (chapters 3,4,5,6) Logic (chapters 8,9,10) Learning (chapters 18,20) See (online) syllabus for more detailed course outline (we may stray from the outline depending on how things go).

5 Outline Course overview What is AI? A brief history
The state of the art

6 What is AI? But what is intelligence?
something not entirely well-defined that helps to distinguish what we call animate objects from what we call inanimate objects But when does an object become animate? Does learning play a role? (can an object be intelligent without learning?) Is “living” a necessary condition? Are there any non-living objects in the world you might call intelligent?

7 What is AI? What tasks require intelligence?
The easy (or seemingly mundane) Perception (vision, speech) Natural Language (understanding, generation, translation) Common sense reasoning rational thought, causality, etc. Robotics/Motor skills

8 What is AI? What tasks require intelligence? The formal
Games (chess, backgammon, checkers, go) Mathematics (geometry, logic, integral calculus, theorem proving, program correctness checkers)

9 What is AI? What tasks require intelligence? The expert
Engineering (design, fault finding, manufacturing planning) Scientific analysis and data interpretation, data mining, problem finding Medical diagnosis (doctors) Financial analysis (predict the stock market) Forensic Science Legal Analysis

10 What is AI? What can Humans do? Object recognition:

11 Object Recognition Sometimes it is a continuum.
Escher, Liberation, 1955 What is foreground/background? Escher, Mosaic, 1957

12 Object Recognition Why we need uncertainty. Is it a face, a vase, or both?

13 What is AI? What can Humans do? Speech Recognition:

14 What is AI? Views of AI fall into four categories:
Vertical Axis: Thinking  Acting Horizontal Axis: Humanly  Rationally The textbook advocates "acting rationally“ this is also an engineering perspective. What is important to get the problem solved. Acting or being human? To build systems, we care only about acting. We next consider each of the four above. Thinking humanly Thinking Rationally Acting humanly Acting Rationally

15 Acting humanly: Turing Test
Thinking humanly Thinking Rationally Acting humanly Acting Rationally Acting humanly: Turing Test Alan Turing (1950) "Computing machinery and intelligence": "Can machines think?"  "Can machines behave intelligently?" Operational test for intelligent behavior: the Imitation Game Needs: natural language processing, knowledge representation, automated reasoning, machine learning, computer vision, speech recognition, robotics Turing 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

16 Thinking humanly: cognitive modeling
Thinking Rationally Acting humanly Acting Rationally Thinking humanly: cognitive modeling 1960s "cognitive revolution": information-processing “psychology” replaced orthodoxy of behaviorism compute as a human would compute Requires scientific theories of internal activities of the brain what level of abstraction? “Knowledge”, “circuits”, only need a “model” of the process, don’t need to replicate the process (e.g., neuro-) How to validate? Requires Predicting and testing behavior of human subjects (top-down), or Direct identification from neurological data (bottom-up) Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now considered distinct from AI (which is more related to computer science) Both share with AI: existing theories do not yet explain anything close to resembling true human-level general intelligence. We have a *long* way to go. So the various doctrines share a basic principal direction but are considered different (sub-)fields.

17 Thinking rationally: "laws of thought"
Thinking humanly Thinking Rationally Acting humanly Acting Rationally Thinking rationally: "laws of thought" Irrefutable (prescriptive rather than descriptive) reasoning processes that must occur (logic) Aristotle: what are correct arguments/thought processes? Logical forms that rational thinking possesses. Ex: “Socrates is a man, all men are mortal, therefore Socrates is mortal.” 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 (which is what we care about in this class) Direct line through mathematics and philosophy to modern AI Problems with this approach: Not all intelligent behavior is mediated by logical deliberation (many “intelligent” people apparently behave “irrationally”) What is the purpose of thinking? What thoughts should I have out of all thoughts (logical or otherwise) that I could have? Hard to say

18 Acting rationally: rational agent
Thinking humanly Thinking Rationally Acting humanly Acting Rationally Acting rationally: rational agent Rational behavior: doing the right thing but we don’t care as much how it is happening as long as it undeniably is happening. 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 Aristotle (Nicomachean Ethics): Every art and every inquiry, and similarly every action and pursuit, is thought to aim at some good.

19 Rational agents An agent is a key idea in this course.
An agent is an entity that perceives and acts This course is about designing rational agents agents, build to in one way or another, act “rational” Abstractly, an agent is a function from percept histories to actions: [f: P*  A] Is this real intelligence? Are we deterministic? Practically: For any given class of environments and tasks, we seek the agent (or class of agents) with the best performance in a given environment at a particular time. Caveat: computational limitations make perfect rationality unachievable (even if we had perfect f) Some agent “functions” might be computationally intractable Goal: design best program for given machine resources

20 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, optimization Psychology phenomena of perception and motor control, experimental techniques, psycho-* Economics utility, decision theory, game theory Linguistics knowledge representation, grammar Neuroscience physical substrate for mental activity Control theory design systems that maximize an objective function over time, temporal processes Computer building fast computing systems engineering Electrical signal processing, acoustics, sound Engineering

21 Abridged history of AI McCulloch & Pitts: Boolean circuit model of brain 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 1966—73 AI discovers computational complexity Neural network research almost disappears 1969—79 Early development of knowledge-based systems AI becomes an industry Neural networks return to popularity AI becomes a science Uncertain reasoning is acknowledged (Pearl) The emergence of intelligent agents (our text!!) Human-level AI is back to popularity

22 State of the art Which of the following can be done by computer at the present time? Play a decent game of table tennis Drive safely along a curving mountain road Drive safely along University Avenue Buy a week's worth of groceries on the web Buy a week's worth of groceries at Whole Foods Market Play a decent game of bridge Discover and prove a new mathematical theorem Design and execute a research program in molecular biology Write an intentionally funny story Give competent legal advice in a specialized area of law Translate spoken English into spoken Swedish in real time Converse successfully with another person for an hour Perform a complex surgical operation Unload any dishwasher and put everything away Recognize fluently spoken conversational speech without mistake

23 State of the art Which of the following can be done by computer at the present time? Play a decent game of table tennis Drive safely along a curving mountain road Drive safely along University Avenue Buy a week's worth of groceries on the web Buy a week's worth of groceries at Whole Foods Market Play a decent game of bridge Discover and prove a new mathematical theorem Design and execute a research program in molecular biology Write an intentionally funny story Give competent legal advice in a specialized area of law Translate spoken English into spoken Swedish in real time Converse successfully with another person for an hour Perform a complex surgical operation Unload any dishwasher and put everything away Recognize fluently spoken conversational speech without mistake

24 State of the art Deep Blue defeated the reigning world chess champion Garry Kasparov in 1997 Proved a mathematical conjecture (Robbins conjecture) unsolved for decades (1997), proved in the affirmative are all Robbin’s algebras boolean? Algebra that satisfies commutatively, associatively, and Robbins equation: n(n(x + y) + n(x + n(y))) = x “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 (including myself) Question: So do these things really require intelligence? How does the chess program work so well?


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