Edward A. Feigenbaum

References

(Feigenbaum, 1984) ⇒ E. A. Feigenbaum. (1984). “Knowledge Engineering: The applied side of artificial intelligence.” In: Annals of the New York Acedemy of Sciences, 246.

(Feigenbaum & McCorduck, 1983) ⇒ Edward A. Feigenbaum, and Pamela McCorduck. (1983). “The Fifth Generation (1st edition).” Addison-Wesley. ISBN:9780201115192
- QUOTE: KE is an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise.

(Barr & Feigenbaum, 1981) ⇒ Avron Barr, and Edward A. Feigenbaum. (1981). “The Handbook of Artificial Intelligence, Volume 1.” Kaufman
- QUOTE: When the system is required to do something that it has not been explicitly told how to do, it must reason - it must figure out what it needs to know from what it already knows. For instance, suppose an information retrieval program 'knows' only that Robins are birds and that All birds have wings. Keep in mind that for a system to know these facts means only that it contains data structures and procedures that would allow it to answer the questions: Are Robins birds? ⇒ Yes. Do all birds have wings? ⇒ Yes. If we then ask it, Do robins have wings? the program must reason to answer the query. In problems of any complexity, the ability to do this becomes increasingly important. The system must be able to deduce and verify a multitude of new facts beyond those it has been told explicitly.

(Buchanan & Feigenbaum, 1978) ⇒ Bruce G. Buchanan, Edward A. Feigenbaum. (1978). “Dendral and Meta-Dendral: Their Applications Dimension.” In: Artificial Intelligence, 11(1-2).

(Buchanan et al., 1971b) ⇒ Bruce G. Buchanan, Edward A. Feigenbaum, and Joshua Lederberg. (1971). “A Heuristic Programming Study of Theory Formation in Science.” In: IJCAI 1971: 40-50
(Buchanan et al., 1971a) ⇒ Bruce G. Buchanan, Edward A. Feigenbaum, and Joshua Lederberg. (1971). “A Heuristic Programming Study of Theory Formation in Science.” Technical Report: CS-TR-71-221, Stanford University
- The Meta-DENDRAL program is a vehicle for studying problems of theory formation in science. The general strategy of Meta-DENDRAL is to reason from data to plausible generalizations and then to organize the generalizations into a unified theory. Three main subproblems are discussed: (1) explain the experimental data for each individual chemical structure, (2) generalize the results from each structure to all structures, and (3) organize the generalizations into a unified theory. The program is built upon the concepts and programmed routines already available in the Heuristic DENDRAL performance program, but goes beyond the performance program in attempting to formulate the theory which the performance program will use.