CSci 4511w: Class Notes
|Intro to AI
|Logic and Knowledge Representation
Material will be added to this page during the semester, in particular
while a topic is being covered.
General resources on AI and Computer Science
Applets and demo programs
Intro to AI
- The term Artificial Intelligence was first used in 1955
by John McCarthy in the
Proposal for the Dartmouth Summer Research Project on Artificial
Intelligence to the Rockfeller Foundation, by
John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon.
The proposal starts like this:
"We propose that a two-month, ten man study of artificial intelligence be
carried out during the summer of 1956 at Dartmouth College in Hanover, New
Hampshire. The study is to proceed on the basis of the conjecture that
every aspect of learning or any other feature of intelligence can in
principle be so precisely described that a machine can be made to simulate
An attempt will be made to find how to make machines use language, form
abstractions and concepts, solve kinds of problems now reserved for
humans, and improve themselves. We think that a significant advance can
be made in one or more of these problems if a carefully selected group of
scientists work on it together for a summer.
[Additional attendees were Trenchard More, Arthur Samuel, Oliver Selfridge,
Ray Solomonoff, Alen Newell, and Herbert Simon.]
- For a short introduction to different meanings of the term artificial
read the first pages of
"Natural and Artificial Intelligence" by Robert Sokolowski
Artificial Intelligence is an attempt to prove the Physical-Symbol
System Hypothesis (PSSH).
From Allen Newell and Herbert Simon, Turing Award winners,
"Computer Science as Empirical Inquiry: Symbols and Search,"
Communications of the ACM, March 1976, pp 113-126.
"A physical symbol system consists of a set of entities, called symbols,
which are physical patterns that can occur as components of another type
of entity called an expression (or symbol structure). Thus, a symbol
structure is composed of a number of instances (or tokens) of symbols
related in some physical way (such as one token being next to another).
At any instant of time the system will contain a collection of these
symbol structures. Besides these structures, the system also contains a
collection of processes that operate on expressions to produce other
expressions: processes of creation, modification, reproduction and
In the paper they state the Physical Symbol System Hypothesis:
"A physical symbol system has the necessary and sufficient means for
general intelligent action.
By necessary we mean that any system that exhibits intelligence will
prove upon analysis to be a physical symbol system.
By sufficient we mean that any physical symbol system of sufficient
size can be organized further to exhibit general intelligence.
By general intelligent action we wish to indicate the same scope of
intelligence as we see in human action."
- Look at What is
Artificial Intelligence?, a paper from John McCarthy.
For another view, look at
What is Artificial Intelligence?, an on-line philosophical
introduction to AI by Jack Copeland. The article includes some history
of AI, the Turing test, and more. Easy to read.
- The original paper by A. M. Turing,
Computing machinery and intelligence.
Mind, 59, pp 433-460, 1950. Read how he described the Turing test and
- Notes on search algorithms. The
description of the algorithms in these notes is taken from J. Pearl,
"Heuristics", Addison-Wesley, 1984.
- Examples of how to do depth-first search
- Constraint propagation
- An example from Peter Norvig of how to use constraints to solve Sudoku Puzzles using Python.
- Do you want to know how many colors you need to color a planar map
so that no two adjacent regions (that share more than a common point)
do not have the same color?
The problem is called the map coloring problem. It is solved by the
four color theorem.
- Minimax and alpha-beta pruning
- Practical applications of search algorithms
- A complex search problem: searching for airfares. ITAsoftware
is the leader in producing software that is used to search for airfares,
schedule, and availability of flights. To get a glimpse at the
complexity, think that there are 10,000 paths from San Franscisco to
Boston, and for each path about 10,000 ways of pricing the itinerary.
How MapQuest Works
Logic, Resolution, and Knowledge Representation
Notes on hot to do resolution with propositional
calculus and a detailed example of using resolution.
Notes on how to do unification.
A detailed example of translating from English
to predicate calculus with comments on the scope of quantifiers.
Try answering these practice questions on
resolution. Once you are done, check out the
answer to one of the questions.
USA, Appellee v. Janet Leslie Cooper Byrnes, Appellant on the Small
Bird Act we read in class.
- The Semantic Web
- The Semantic Web Wiki
Searching the Deep Web", Comm of the ACM, Vol 51, N 10, 2008, pp 14-15.
It is a short article on how to do deep web search without having to
require semantic web markup.
- Twine uses RDIF and OWL
to help organizing, sharing, and discovering knowledge on the web.
- Notes on the STRIPS language, assumptions
- Try the applet at
It lets you use the STRIPS representation for actions and states,
and runs a planning algorithm to produce a plan. It works only in the
blocks world, but has a nice graphical interface that let's you follow
what happens step-by-step while constructing the plan and let's you
execute the plan step by step. Very cute!
- A short description and figures for the mutexes
used in Graphplan.
- Useful papers on planning:
- The paper by D. Weld,
"An introduction to least commitment planning",
AI Magazine, Winter 1994, pp 27-61
is a well written tutorial on least commitment
planning algorithms, and includes detailed examples.
- A more recent paper by D. Weld,
"Recent Advances in AI Planning", AI Magazine, 1999
(postscript - 50 pages)
describes advances in AI planning (it includes Graphplan and SAT
- The original paper on Graphplan by Avrim Blum and Merrick Furst
"Fast planning through planning graph analysis,"
Artificial Intelligence, vol 90, pp 281-300, 1997
is available from
http://www.cs.cmu.edu/~avrim/graphplan.html, the Graphplan home page.
- To learn about and to use a planner based on SAT, look at
This planner combines graphplan with satplan. On the page you'll
find links to papers such as
Henry Kautz, David McAllester, and Bart Selman,
"Encoding Plans in Propositional Logic", Proc. KR-96.
Copyright: © 2008 by the Regents of the University
Department of Computer Science and
Engineering. All rights reserved.
Comments to: Maria Gini
Changes and corrections are in red.
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