SAINT

The invention:



Taking its name from the acronym for symbolic automatic

integrator, SAINT is recognized as the first “expert system”—

a computer program designed to perform mental tasks requiring

human expertise.



The person behind the invention:



James R. Slagle (1934-1994), an American computer scientist









 The Advent of Artificial Intelligence



In 1944, the Harvard-IBM Mark I was completed. This was an

electromechanical (that is, not fully electronic) digital computer

that was operated by means of coding instructions punched into

paper tape. The machine took about six seconds to perform a multiplication

operation, twelve for a division operation. In the following

year, 1945, the world’s first fully electronic digital computer,

the Electronic Numerical Integrator and Calculator (ENIAC),

became operational. This machine, which was constructed at the

University of Pennsylvania, was thirty meters long, three meters

high, and one meter deep.

At the same time that these machines were being built, a similar

machine was being constructed in the United Kingdom: the automated

computing engine (ACE).Akey figure in the British development

was Alan Turing, a mathematician who had used computers

to break German codes during World War II. After the war, Turing

became interested in the area of “computing machinery and intelligence.”

He posed the question “Can machines think?” and set the

following problem, which is known as the “Turing test.” This test

involves an interrogator who sits at a computer terminal and asks

questions on the terminal about a subject for which he or she seeks intelligent

answers. The interrogator does not know, however, whether

the system is linked to a human or if the responses are, in fact, generated

by a program that is acting intelligently. If the interrogator cannot

tell the difference between the human operator and the computer

system, then the system is said to have passed the Turing test

and has exhibited intelligent behavior.





SAINT: An Expert System





In the attempt to answer Turing’s question and create machines

that could pass the Turing test, researchers investigated techniques

for performing tasks that were considered to require expert levels of

knowledge. These tasks included games such as checkers, chess, and

poker. These games were chosen because the total possible number of

variations in each game was very large. This led the researchers to

several interesting questions for study. How do experts make a decision

in a particular set of circumstances? How can a problem such as

a game of chess be represented in terms of a computer program? Is it

possible to know why the system chose a particular solution?

One researcher, James R. Slagle at the Massachusetts Institute of

Technology, chose to develop a program that would be able to solve

elementary symbolic integration problems (involving the manipulation

of integrals in calculus) at the level of a good college freshman.

The program that Slagle constructed was known as SAINT, an

acronym for symbolic automatic integrator, and it is acknowledged

as the first “expert system.”

An expert system is a system that performs at the level of a human

expert. An expert system has three basic components: a knowledge

base, in which domain-specific information is held (for example, rules

on how best to perform certain types of integration problems); an inference

engine, which decides how to break down a given problem utilizing

the rules in the knowledge base; and a human-computer interface

that inputs data—in this case, the integral to be solved—and

outputs the result of performing the integration. Another feature of expert

systems is their ability to explain their reasoning.

The integration problems that could be solved by SAINT were

in the form of elementary integral functions. SAINT could perform

indefinite integration (also called “antidifferentiation”) on these

functions. In addition, it was capable of performing definite and

indefinite integration on trivial extensions of indefinite integration.

SAINT was tested on a set of eighty-six problems, fifty-four of

which were drawn from the MIT final examinations in freshman

calculus; it succeeded in solving all but two. Slagle added more

rules to the knowledge base so that problems of the type it encountered

but could not solve could be solved in the future.

   The power of the SAINT system was, in part, based on its ability

to perform integration through the adoption of a “heuristic” processing

system.Aheuristic method is one that helps in discovering a

problem’s solution by making plausible but feasible guesses about

the best strategy to apply next to the current problem situation. A

heuristic is a rule of thumb that makes it possible to take short cuts

in reaching a solution, rather than having to go through every step

in a solution path. These heuristic rules are contained in the knowledge

base. SAINT was written in the LISP programming language

and ran on an IBM 7090 computer. The program and research were

Slagle’s doctoral dissertation.



 Consequences



 The SAINT system that Slagle developed was significant for several

reasons: First, it was the first serious attempt at producing a

program that could come close to passing the Turing test. Second, it

brought the idea of representing an expert’s knowledge in a computer

program together with strategies for solving complex and difficult

problems in an area that previously required human expertise.

Third, it identified the area of knowledge-based systems and

 showed that computers could feasibly be used for programs that

did not relate to business data processing. Fourth, the SAINT system

showed how the use of heuristic rules and information could

lead to the solution of problems that could not have been solved

previously because of the amount of time needed to calculate a solution.

SAINT’s major impact was in outlining the uses of these techniques,

which led to continued research in the subfield of artificial

intelligence that became known as expert systems.





  

James R. Slagle



James R. Slagle was born in 1934 in Brooklyn,NewYork, and

attended nearby St. John’s University. He majored in mathematics

and graduated with a bachelor of science degree in 1955,

also winning the highest scholastic average award. While earning

his master’s degree (1957) and doctorate (1961) at the Massachusetts

Institute of Technology (MIT), he was a staff mathematician

in the university’s Lincoln Laboratory.

Slagle taught in MIT’s electrical engineering department

part-time after completing his dissertation on the first expert

computer system and then moved to Lawrence-Livermore

National Laboratory near Berkeley, California. While working

there he also taught at the University of California. From 1967

until 1974 he was an adjunct member of the computer science

faculty of Johns Hopkins University in Baltimore, Maryland,

and then was appointed chief of the computer science laboratory

at the Naval Research Laboratory (NRL) inWashington, D.C., receiving

the Outstanding Handicapped Federal Employee of the

Year Award in 1979. In 1984 he was made a special assistant in

the Navy Center for Applied Research in Artificial Intelligence

at NRL but left in 1984 to become Distinguished Professor of

Computer Science at the University of Minnesota.

In these various positions Slagle helped mature the fledgling

discipline of artificial intelligence, publishing the influential

book Artificial Intelligence in 1971. He developed an expert system

designed to set up other expert systems—A Generalized

Network-based Expert System Shell, or AGNESS. He also worked

on parallel expert systems, artificial neural networks, timebased

logic, and methods for uncovering causal knowledge in

large databases. He died in 1994.