Transcript Slide 1

CS 416
Artificial Intelligence
Lecture 2
Introduction
CS at UVa
$11M in research grants each year
• Top 5% of research is funded by NSF
• Faculty trips to NSF set national funding priorities
• Free MSFT Visual Studio for all students
75% faculty growth in past six years
Undergrad research awards from CRA
Highest starting salary (in SEAS) for ugrads
Textbook
This is a great book
• 2nd edition released three years ago
• Most widely used in U.S. universities
• It’s so good….
– I’m going to make you read it!
Homework
• Read chapters 1 and 2
Survey Results
• Languages
– Supermajority prefers C++
– Three people indicated they’ll need C++ help
– LISP?
• Math
– Many w/o stat
– 7 w/o diffyq
– 14 w/o linear algebra
• 5 people w/o GUI experience
• 4 people w/o MSFT Windows
• 14 people don’t play so many video games
• Where have you done the most programming?
– 216 – 17
– Graphics – 15
– 201/202 – 6
– OS – 2
• AI apps
– Chess, google, spam filter, finance, chatterbot, games,
vacuum
 12% of CPU for AI tasks in games?
 More about magic tricks than AI?
iRoomba - Rodney Brooks’ (MIT) company
Languages
• Is AI special in its PL needs?
– AI research used to be more symbolic
 A language had to make it easy to create symbols and to
manipulate them
 Some symbols would operate on other symbols
 LISP supported “programs as data” and dynamic typing
– Modern AI is more quantitative
 No language has emerged with an advantage
• Our language choice cannot distract from learning AI
Languages
• C++ - Common industry language
• C – gets a little closer to real-time OS
• Perl – the duct tape of the Internet – “makes the easy things easy and
the hard things impossible” – “there’s more than one way to do it”
• Python – “there’s only one way to do it”
• Scheme – easy to learn but difficult to extend
• Common Lisp – “the programmable programming language” – nontrivial
to learn but a decidedly different experience from programming in
imperative languages
What is expected of you
You’ll have to do math
• Neural network update function
wi  j  

x ,c T
P x ,c
2wi  j
• Multidimensional function
minimization
• Probability – Bayes’ Rule
• We will teach necessary parts of
statistics and linear algebra
P ( X | Y ) P (Y )
P (Y | X ) 
P( X )
Calculus expected.
Probability and Linear
Algebra beneficial.
What is expected of you
You have to program
• The programming assignments are non-trivial
– C++
– Requires integration with existing code libraries
– Input/output handling (images, for example)
– We do not teach programming in this course
CS 216 expected.
Additional programming
experience beneficial.
AI Systems
• Thermostat
• Tic-Tac-Toe
• Your car
• Chess
• Google
• Babblefish
• This thing
– Asimo
Examples
• Chess: Deep Junior (IBM) tied Kasparov in 2003 match
ATR’s DB Android
Ritsumeikan University
RHex Hexapod
Honda’s Asimo
AI Techniques
• Rule-based
• Fuzzy Logic
• Neural Networks
• Genetic Algorithms
• Exhaustive search
• Expert Systems
• Logic
How to Categorize These Systems
Systems that think like humans
Systems that act like humans
Systems that think rationally
Systems that act rationally
Systems that think/act like humans
It’s hard to study things you can’t observe…
• How can I know how you think?
– Observation is difficult (changing with fMRI). For the most part, you
are a “black box”
– Cognitive Science
• How can I know how you act?
– Observation is possible, but hard to control all aspects of
experimental conditions.
– Turing Test
Alan Turing – “Building a Brain”
World War II motivated computer advances
• Code breaking (1943, Colossus) – Used to decipher
telegrams encrypted using Germany’s encryption machine
• Electronic Numerical Integrator and Computer (ENIAC, 1946)
Turing greatly involved with British efforts to build
computers and crack codes (Bletchley Park)
• Arrested for being a homosexual in 1952 and denied security clearance
• Committed suicide in 1954
Systems that think/act rationally
Rely on logic itself rather than human to
measure correctness
• Thinking rationally (logically)
– Socrates is a human; All humans are mortal; Socrates is mortal
– Logic formulas for synthesizing outcomes
• Acting rationally (logically)
– Even if method is illogical, the observed behavior must be
rational
Perspective of this Course
We will investigate the general principles of
rational agents
• Not restricted to human actions and human environments
• Not restricted to human thought
• Not confined to only using laws of logic
• Anything goes so long as it produces rational behavior
What is AI?
The use of computers to solve problems that
previously could only be solved by applying human
intelligence…. thus something can fit this definition
today, but, once we see how the program works and
understand the problem, we will not think of it as AI
anymore (David Parnas)
Foundations - Philosophy
• Aristotle (384 B.C.E.) – Author of logical syllogisms
• da Vinci (1452) – designed, but didn’t build, first mechanical
calculator
• Descartes (1596) – can human free will be captured by a
machine? Is animal behavior more mechanistic?
• Necessary connection between logic and action is
discovered
Foundations - Mathematics
• Leveraging uncertainty (Cardano 1501)
• Boolean logic (Boole, 1847)
• Analysis of limits to what can be computed
– Intractability (1965) – time required to solve problem
scales exponentially with the size of problem instance
– NP-complete (1971) – Formal classification of problems as
intractable
Foundations - Economics
•
Game Theory – study of rational behavior in small games
•
Operations Research – study of rational behavior in
complex systems
•
Herbert Simon (1916 – 2001) – AI researcher who received
Nobel Prize in Economics for showing people accomplish
satisficing solutions, those that are good enough
Foundations - Neuroscience
How do brains work?
• Early studies (1824) relied on injured and abnormal people to understand what
parts of brain do
• More recent studies use accurate sensors to correlate brain activity to human
thought
– By monitoring individual neurons, monkeys can now control a computer
mouse using thought alone
– Melody Moore at GaState – “locked-in syndrome”
• (Gordon) Moore’s law states computers will have as many gates as humans
have neurons in 2020
• How close are we to having a mechanical brain?
– Parallel computation, remapping, interconnections, binary vs. gradient…
Foundations - Psychology
• Helmholtz and Wundt (1821) – started to make psychology a
science by carefully controlling experiments
• The brain processes information (1842)
– Sense  Think  Act
– Cognitive science started at a MIT workshop in 1956 with
the publication of three very influential papers
Foundations – Control Theory
• Machines can modify their behavior in response to the
environment (sense / action loop)
– Water-flow regulator (250 B.C.E), steam engine governor,
thermostat
• The theory of stable feedback systems (1894)
– Build systems that transition from initial
state to goal state with minimum energy
– In 1950, control theory could only describe
linear systems and AI largely rose as a
response to this shortcoming
Foundations - Linguistics
Speech demonstrates so much of human
intelligence
• Analysis of human language reveals thought taking place in
ways not understood in other settings
– Children can create sentences they have never heard
before
– Language and thought are believed to be tightly
intertwined