Edward A ("Ed") Feigenbaum

Edward Feigenbaum and Raj Reddy have been seminal leaders in defining the emerging field of applied artificial intelligence, and in demonstrating its technological significance.

Edward Albert Feigenbaum is widely known as the father of expert systems. Expert systems are computer programs that act intelligently by using the specially encoded knowledge of experts in fields as diverse as chemistry, medical diagnosis and therapy, geologic exploration, hardware and software trouble-shooting and business practice.

Feigenbaum was born on January 20, 1936 in Weehawken, New Jersey. He learned to read very early, and as a young child became quite skilled in using his stepfather’s Monroe calculator. His stepfather took him on frequent visits to the Hayden Planetarium of the American Museum of Natural History, from which he developed an early interest in astronomy, and in science generally. His favorite pre-college courses were math, physics, and chemistry.

He received a scholarship to attend the Carnegie Institute of Technology (now Carnegie Mellon University) in Pittsburgh, Pennsylvania. Among the courses he took was one taught by Herbert Simon (1975 Turing Award recipient) called “Mathematical Models in the Social Sciences.” His first introduction to computers was digesting the manual Simon gave him for the IBM 701, an early vacuum-tube computer.

Feigenbaum stayed at Carnegie Tech and did a PhD dissertation under Simon’s supervision, on a computer model that simulates how humans learn nonsense syllables. He called the computer program implementing the model EPAM: Elementary Perceiver and Memorizer. EPAM is still considered a leading theory of memory organization in cognitive science. It was also one of the first programs to demonstrate that a computer could learn. The basic mechanism of EPAM, a decision tree (which Feigenbaum called a “Discrimination Net”), is one of the most important computational structures for storing and indexing data. It is used extensively in machine learning research, and in data mining. At Carnegie, Feigenbaum also participated in the implementation of IPL-V, the first publicly available list-processing language.

After completing his dissertation in 1960, he accepted a position at the University of California, Berkeley, where he taught courses on organization theory, and on computer simulation of intelligent behavior. For the latter, which included topics in what now is called artificial intelligence, he and colleague Julian Feldman distributed photocopies of early papers on computer intelligence. In 1963, these papers, plus some others specially commissioned, were published in an influential volume titled Computers and Thought, which was republished in 1995 by AAI Press in conjunction with MIT Press.[1]

After five years at Berkeley, Feigenbaum joined the faculty at Stanford University. He was motivated primarily by the desire to shift away from the science of how humans think, which occupied much of his time at Berkeley, to the technology of getting computers to think—a technology that was the focus of John McCarthy, who had recently moved to Stanford from MIT.

Feigenbaum was interested in the problem of “induction”, and in particular how to get computers to create theories from data− theories that not only explained the particular data on which the theory was based, but could also make predictions about new data. He thought progress could best be made by finding and working on a specific problem. As he later put it, I needed a ‘task environment—a sandbox in which to specifically work out ideas in detail. Joshua Lederberg, a Nobel Prize winner in genetics at Stanford was doing work on analyzing mass spectrograms of amino acids, and suggested to Feigenbaum the problem of inducing the three-dimensional structure of these chemicals from their mass spectrograms.

Following up on Lederberg’s suggestion, Feigenbaum and colleagues developed Heuristic DENDRAL, a computer program that could guess the geometrical structure of complex chemical compounds given their chemical formulae and their mass spectrogram data. Heuristic DENDRAL discovered some previously unknown structures, and these discoveries were published in a series of papers in the Journal of the American Chemical Society. The program used rules, elicited from chemists, about how a mass spectrometer fragmented compounds into sub-structures. From knowledge of the sub-structures, Heuristic DENDRAL was able to deduce the most plausible overall structure of the compound. Later, his META-DENDRAL program was even able to automatically deduce new rules from chemical data that Heuristic DENDRAL could use to improve its performance.

From his work on Heuristic DENDRAL, Feigenbaum became convinced about the importance of endowing computer programs with knowledge in the form of rules and procedures to guide the process of problem solving. He is credited with inventing and being the first to use the phrases “Knowledge is Power,” “Expert Systems,” “Knowledge Engineering,” and “Expertise” in connection with AI programs. Many researchers in artificial intelligence had previously focused on formal “reasoning” methods. Feigenbaum shifted the emphasis to “knowledge,” and that shift was critically important to future successes in artificial intelligence.

After their work on chemical structures, Feigenbaum’s laboratory went on to develop expert-system programs in medicine (MYCIN, PUFF, ONCOCIN), molecular genetics (MOLGEN), X-ray crystallography (CHRYSALIS), and analysis of pulmonary function (PUFF). It also developed the first transportable general-purpose expert system “shell” (EMYCIN). With the aid of computer scientists, experts in different subject areas could populate EMYCIN with their specialized knowledge in the form of rules, and then the knowledge-augmented system could be applied to different problem areas.

Feigenbaum and his wife Penny Nii also did important work for the U.S. Defense Department on applying expert-system technology to the problem of interpreting data from ocean-based hydro-acoustic sensors, resulting in a computer program called HASP.

As one would expect from an academic scholar engaged in leading edge research, Feigenbaum guided a large number of graduate students into successful scientific, technical, and business careers. Among these were Edward (Ted) Shortliffe, Randall Davis, Peter Friedland, Mark Stefik, Bill Van Melle, and Jan Aikens. He also had a number of important collaborators, including Joshua Lederberg, Bruce Buchanan, Carl Djerassi, Robert Engelmore, Robert Lindsay, and Georgia Sutherland. His personal style always involved collaborating with extremely capable colleagues and students, guiding and inspiring the work with key ideas.

Feigenbaum has also been involved in administrative and professional activities. He was the director of Stanford University’s Computer Center during the 1960s, and served as the chair of Stanford’s Department of Computer Science from 1976 to 1981. He played a key role in the formation of SUMEX—a national computing resource at Stanford supported by, and aiding, the U. S. National Institutes of Health.

Feigenbaum is a Fellow and Past President of the American Association for Artificial Intelligence (now called the Association for the Advancement of Artificial Intelligence). He has served on the National Science Foundation Computer Science Advisory Board, on the National Research Council’s Computer Science and Technology Board, and as a member of the Board of Regents of the National Library of Medicine. He has taught at Stanford’s Kyoto campus and has lectured frequently in Japan and Europe about artificial intelligence and its applications. He maintains strong links with Japanese universities. From 1994 to 1997, he served as Chief Scientist of the U. S. Air Force.

Feigenbaum co-founded three companies involved in applied artificial intelligence, IntelliCorp, Teknowledge, and Design Power Inc. He continues as an adviser to companies employing AI and related computer technology.

His activities in teaching, research, scholarship, business, and public service have had lasting impact in technical, business, and government communities. His accomplishments have led to many awards and honors. In addition to being a co-recipient (with Raj Reddy) of the ACM Turing Award in 1994, he is a Fellow of the American College of Medical Informatics, of the American Institute of Medical and Biological Engineering, and of the American Association for the Advancement of Science. He is a member of the National Academy of Engineering and of the American Academy of Arts and Sciences.

For an article based on an interview with Feigenbaum, see Len Shustek, “An Interview with Ed Feigenbaum” Communications of the ACM, Vol. 53 No. 6, pp. 41-45, June 2010. Available online here.

Author: Nils J. Nilsson