DENDRAL was an early
expert system intended at analyzing and recognizing complicated chemical
substances, developed by Nobel Laureate Joshua Lederberg and computer scientist
Edward Feigenbaum.
DENDRAL (meaning tree in Greek) was created by Feigenbaum
and Lederberg at Stanford University's Artificial Intelligence Laboratory in
the 1960s.
There was considerable expectation at the time that
computers capable of analyzing alien buildings for evidence of life might aid
NASA's 1975 Viking Mission to Mars.
DEN DRAL relocated to Stanford's Chemistry Department in the
1970s, where it was directed by Carl Djerassi, a well-known scientist in the
area of mass spectrometry, until 1983.
Because there was no overarching theory of mass
spectrometry, molecular chemists used rules of thumb to analyze the raw data
obtained by a mass spectrometer to identify organic chemicals.
Computers, according to Lederberg, might make organic
chemistry more methodical and predictable.
He began by creating a comprehensive search engine.
The provision of heuristic search criteria was Feigenbaum's
first contribution to the project.
These guidelines codified what scientists already knew about
mass spectrometry.
As a consequence, a groundbreaking AI system was created
that provided the most likely responses rather than all potential ones.
According to Timothy Lenoir, a historian of science, DENDRAL
"would analyze the data, generate a list of candidate structures, predict
the mass spectra of those structures using mass spectrometry theory, and select
as a hypothesis the structure whose spectrum most closely matched the
data" (Lenoir 1998, 31).
Around 1968, Feigenbaum said, he created the phrase
"expert system." Because it incorporates scientific competence,
DENDRAL is called an expert system.
Computer scientists took the information that human chemists
had retained in their working minds and made it explicit in DEN DRAL's IF-THEN
search criteria.
An expert system, in technical terms, is a computer system
that has a clear separation between the knowledge base and the inference
engine.
This, in theory, enables human specialists to examine the
rules of a software like DENDRAL, comprehend its structure, and provide
suggestions on how to improve it.
Starting in the mid-1970s, the favorable findings of DENDRAL
led to a steady quadrupling of Feigenbaum's Defense Advanced Research Projects
Agency funding for artificial intelligence research.
DENDRAL grew at the same rate as the field of mass
spectrometry.
After outgrowing Lederberg's expertise, the system started
to absorb Djerassi's and others' information from his lab.
As a result, both chemists and computer scientists gained a
better understanding of the underlying structure of organic chemistry and mass
spectrometry, enabling the area to take a significant stride toward theory
development.
~ Jai Krishna Ponnappan
You may also want to read more about Artificial Intelligence here.
See also:
Expert Systems; MYCIN MOLGEN.
Further Reading:
Crevier, Daniel. 1993. AI: The Tumultuous History of the Search for Artificial Intelligence. New York: Basic Books.
Feigenbaum, Edward. October 12, 2000. Oral History. Minneapolis, MN: Charles Babbage Institute.
Lenoir, Timothy. 1998. “Shaping Biomedicine as an Information Science.” In Proceedings of the 1998 Conference on the History and Heritage of Science Information Systems, edited by Mary Ellen Bowden, Trudi Bellardo Hahn, and Robert V. Williams, 27–45. Medford, NJ: Information Today
