CS-INFO 372: Explorations in Artificial Intelligence. Prof. Carla P. Gomes email@example.com Introduction http://www.cs.cornell.edu/courses/cs372/2008sp. INFO372 – Explorations in Artificial Intelligence Course Administration. Lectures : Tuesday and Thursday - 10:10 - 11:25
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Prof. Carla P. Gomes
Lectures: Tuesday and Thursday - 10:10 - 11:25
Location: Phillips Hall, room 307
Lecturer: Prof. Gomes
Office: 5133 Upson Hall
Phone: 255 9189
Administrative Assistant: Beth Howard
5136 Upson Hall, 255-4188
TAs: Robert Xiao firstname.lastname@example.org
Yunsong Guo <email@example.com>
Robert Xiao firstname.lastname@example.org TBA
Yunsong Guo email@example.com TBA
Office: 5133 Upson Hall
If you need to meet with me at a different time please
schedule an appointment by email.
Wednesdays 12:00 – 1:00 p.m.
Homework is very important. It is the best way for you to learn the material. You are encouraged to discuss the problems with your classmates, but all work handed in should be original, written by you in your own words. No late homework will be accepted
Artificial Intelligence: A Modern Approach (AIMA)
(Second Edition) by Stuart Russell and Peter Norvig
Artificial Intelligence : A New Synthesis
By Nils Nilsson
Principles of Constraint Programming
By Krzysztof Apt
Linear Programming by Vasek Chvatal
philosophy, psychology, and cognitive science
computer science and engineering
mathematics and physics
e.g., foundational issues in logic, methods of reasoning,
mind as physical system, foundations of learning,
Computer science and engineering
e.g., complexity theory, algorithms, logic and inference,
programming languages, and system building (hardware
Mathematics and physics
e.g., statistical modeling, continuous mathematics, Markov
models, statistical physics, and complex systems.
and others, e.g., cognitive science, neuroscience, economics, psychology, linguistics, statistics…
Obtaining an understanding of the human mind is one of the
final frontiers of modern science.
George Boole (1779-1848), Gottlob Frege (1848-1925), and Alfred Tarski (1902-1983)
formalizing the laws of human thought
Alan Turing (1912-1954) , John von Neumann (1903-1957), Claude Shannon (1916-2001)
thinking as computation
John McCarthy (1927- ), Marvin Minsky (1927 - ) , Herbert Simon (1916-2001), and Allen Newell (1927-1992)
the start of the field of AI (1959)
In 1936, Alan Turing, a British mathematician, showed that there exists a relatively simple universal computing device that can perform any computational process.
Computers use such a universal model.
Turing also showed the limits of computation – some problems cannot be computed even with the most powerful computer and even with unlimited amount of time – e.g., Halting problem.
"Can machines think?" "Can machines behave intelligently?"
AI system passes
cannot tell which one
is the machine
1960s ELIZA Joseph Weizenbaum
a friend you could never have before
Eliza: Hello. I am ELIZA. How can I help you?
You: Well I feel sad
Eliza: Do you often feel sad?
You: not very often, but it's becoming more common
Eliza: Please go on.
Turing test identified key research areas in AI:
but does a machine need to act humanly
to be considered intelligent?
far fewer interconnections (wires or synapses)
much faster updates.
Fundamentally different hardware may require fundamentally different algorithms!
A) Ability to interact with the real world
to perceive, understand, and act
speech recognition and understanding
image understanding (computer vision)
B) Reasoning and Planning
modelling the external world
problem solving, planning, and decision making
ability to deal with unexpected problems, uncertainties
C) Learning and Adaptation
We are continuously learning and adapting.
We want systems that adapt to us!
Deep Blue beats the World Chess Champion
I could feel human-level intelligence across the room
-Gary Kasparov, World Chess Champion (human…)
Game 1: 5/3/97: Kasparov wins
Game 2: 5/4/97:Deep Blue wins
Game 3: 5/6/97:Draw
Game 4: 5/7/97:Draw
Game 5: 5/10/97: Draw
Game 6: 5/11/97:Deep Blue wins
“I felt a new kind of
Intelligence” ( across
the board from him)
The value of IBM’s stock
Increased by $18 Billion!
One of the most famous modern computers,
Deep Blue, which defeated Gary Kasparov at chess.
- Drew McDermott
(Game 2 - Deep Blue took an early lead.
Kasparov resigned, but it turned out he could
have forced a draw by perpetual check.)
This was real chess. This was a game any human
grandmaster would have been proud of.
Joel Benjamin grandmaster, member Deep Blue team
“I could feel --- I could smell --- a new kind
of intelligence across the table.”
“Deep Blue hasn't proven anything.”
Deep Blue --- huge transposition tables (100,000,000+),
must be carefully managed.
Robbin’s Algebras are all boolean
A mathematical conjecture (Robbins conjecture) unsolved for decades
The Robbins problem was to determine whether one particular set of rules is powerful enough to capture all of the laws of Boolean algebra. One way to state the Robbins problem in mathematical terms is:
Can the equation not(not(P))=P be derived from the following three equations?
 P or Q = Q or P,
 (P or Q) or R = P or (Q or R),
 not(not(P or Q) or not(P or not(Q))) = P.
[An Argonne lab program] has come up with a major mathematical
proof that would have been called creative if a human had thought of it.
New York Times, December, 1996
For two days in May, 1999, an AI Program called Remote Agent
autonomouslyran Deep Space 1 (some 60,000,000 miles from earth)
better than most humans
Michael Littman et a. 99
October 9, 2005
Stanley and the Stanford RacingTeam
were awarded 2 million dollars for being the
first team to complete the 132 mile
DARPA Grand Challenge course (Mojave Desert).
Stanley finished in just under 6 hours 54 minutes
and averaged over 19 miles per hours on the course.
Focus of Info 372: Problem Solving
Introduce the students to a range of computational modeling
approaches and solution strategies using examples from AI and
Multi-agent formalisms (including adversarial games);
General complete backtrack search;
Satisfiability (SAT); Maximum SAT; Horn
Constraint Satisfaction; Binary Constraint Satisfaction;
Mixed Integer Programming, Linear Programming and
Network Flow Models;