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?