Date of Birth: June 15, 1916
Date of Death: February 9, 2001
Herbert Simon's main interests in computer science were in artificial intelligence, human-computer interaction, principles of the organization of humans and machines is information processing systems, the use of computers to study (by modeling) philosophical problems of the nature of intelligence and of epistemology, and the social implications of computer technology.
Artificial Intelligence. For over forty years Simon had been engaged in building computer simulation models of human processes for handling increasing complex and ill-structured cognitive tasks, including the processes of scientific discovery and the use of visual imagery in thinking. For more detail, see Psychology Home Page.
Information Processing Systems. Computer hardware and software design and the design of human organizations and other social institutions (and for that matter, the organization of biological organisms) have much in common: in the structure of the problems they must confront and the mechanisms they use to solve these problems. Simon had been particularly interested in the limits of parallelism and the very common occurrence of so-called nearly decomposable systems as an answer to the dilemmas of complexity.
Intelligence and Epistemology (how we know). The difficulty of many of the classical problems of philosophy are closely associated with the limits on our ability to look inside the black box (the human head). Today, we have other systems, capable of thinking like humans, whose black boxes are open to inspection. A powerful approach to many of the classical problems is to create an epistemology for computers, to see what light it casts on human epistemology. For more detail, see Philosophy Home Page.
Social Implications. The computer is the most important technological leap since the steam engine, perhaps since the invention of writing or agriculture. All computer scientists have a responsibility to think deeply about the implications of this development (Promethean tool or Pandora's Box?) and to help interpret its implications to the broader public. Some of Simon's economic research was directed toward understanding technological change in general and the information processing revolution in particular. For more detail, see Economics Home Page.
Some Recent and Not-so-recent Publications:
Tabachneck-Schijf, H.J.M., Leonardo, A.M., & Simon, H.A. (1997). CaMeRa: A computational model of multiple representations. Cognitive Science, 21(2), 305-350. [Note: The current version of CaMeRa runs on a Macintosh using either Macintosh Common Lisp or Allegro Common Lisp.]
Simon, H.A. (1997). The Sciences of the Artificial (3rd ed.). Cambridge, MA: The MIT Press, 1997
Simon, H.A. (1996). The patterned matter that is mind. In D.M. Steier & T.M. Mitchell (Eds.), Mind matters: A tribute to Allen Newell (Chapter 11). Mahwah, NJ: Erlbaum.
Kim, J., Lerch, J., & Simon, H.A. (1995). Internal representation and rule development in object-oriented design. ACM Transactions on Computer-Human Interaction, 2(4), 357-390.
Langley, P., & Simon, H.A. (1995). Applications of machine learning and rule induction. Communications of the Association for Computing Machinery, 38(11), 54-64.
Simon, H.A. (1995). Artificial intelligence: an empirical science. Artificial Intelligence, 77(1), 95-127.
Simon, H.A. (1995). Explaining the ineffable: AI on the topics of intuition, insight and inspiration. Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Vol. 1, 939-948.
Simon, H.A. (1995). Machine as mind. In K.M. Ford, C. Glymour, & P.J. Hayes (Eds.), Android epistemology (pp. 23-40). Menlo Park, CA: AAAI/The MIT Press.
Simon, H.A. (1995). Problem forming, problem finding, and problem solving in design. In A. Collen & W.W. Gasparski (Eds.), Design and systems: General applications of methodology (Vol. 3, pp. 245-257). New Brunswick, NJ: Transaction Publishers.
Qin, Y., & Simon, H.A. (1995). Imagery and mental models in problem solving. In J. Glasgow, N.H. Narayanan, & B. Chandrasekaran (Eds.), Diagrammatic reasoning: Computational and cognitive perspectives (pp. 403-434). Menlo Park, CA: AAAI/The MIT Press.
Iwasaki, Y., & Simon, H.A. (1994). Causality and model abstraction. Artificial Intelligence, 67, 143-194.
Druzdzel, M.J., & Simon, H.A. (1993). Causality in Bayesian belief networks. Proceedings of the 9th Annual Conference on Uncertainty in Artificial Intelligence (pp. 3-11). Washington, DC.
Valdes-Perez, R.E., Zytkow, J.M., & Simon, H.A. (1993). Scientific model-building as search in matrix spaces. Proceedings of the 11th National Conference on Artificial Intelligence (pp. 472-478). Menlo Park, CA: AAAI Press.
Kalagnanam, J.A., & Simon, H.A. (1992). Directions for qualitative reasoning. Computational Intelligence, 8(2), 308-315.
Valdes-Perez, R., Simon, H.A., & Murphy, R. (1992). Discovery of pathways in science. In J.M. Zytkow (Ed.), Proceedings of the ML92 Workshop on Machine Discovery, 51-57.
Qin, Y., Mitchell, T.M., & Simon, H.A. (1992). Using EBG to simulate human learning from examples and learning by doing. Proceedings of the Fifth Florida Artificial Intelligence Research Symposium, 235-239.
Kalagnanam, J., Simon, H.A., & Iwasaki, Y. (1991). The mathematical bases for qualitative reasoning. IEEE Expert, 6, 11-19.
Bhandari, I.S., Siewiorek, D.P., & Simon, H.A. (1990). Optimal probe selection in diagnostic search. IEEE Transactions on Systems, Man, and Cybernetics, 20, 990-999.
Shen, W., & Simon, H.A. (1989). Rule creation and rule learning through environmental exploration. Proceedings of the 11th International Joint Conference on Artificial Intelligence, pp. 675-680.
Kulkarni, D., & Simon, H.A. (1988). The processes of scientific discovery: The strategy of experimentation. Cognitive Science, 12, 139-175.
Langley, P., Simon, H.A., Bradshaw, G.L., Zytkow, J.M. (1987). Scientific Discovery: Computational Explorations of the Creative Prcesses. Cambridge, MA: The MIT Press.
Simon, H.A., & Newell, A. (1986). Information processing language V on the IBM 650. Annals of the History of Computing, 8, 47-49.
Simon, H.A. (1983). Search and reasoning in problem solving. Artificial Intelligence, 21, 7-29.
Langley, P., Bradshaw, G.L., & Simon, H.A. (1983). Rediscovering chemistry with the BACON system. In R.S. Michalski, J.G. Carbonell & T.M. Mitchell (Eds.), Machine learning, an artificial intelligence approach (Chap. 10). Palo Alto, CA: Tioga Publishing Co.
Simon, H.A. (1981). Prometheus or Pandora: The influence of automation on society. Computer, 14, 69-74.
Simon, H.A. (1977). Artificial intelligence systems that understand. Proceedings of the Fifth International Joint Conference on Artificial Intelligence, 2, 1059-1073.
Simon, H.A., & Kadane, J. (1977). Optimal problem-solving search: All-or-none solutions. Artificial Intelligence, 6(3), 235-247.
Simon, H.A. (1976). The design of large computing systems as an organizational problem. In P. Verburg, C.A. Malotaux, K.T.A. Halbertsma, & J.L. Boers (Eds.), Organisatiewetenschap en praktijk (pp. 163-180). Leiden: H.E. Stenfert Kroese B.V.
Newell, A., & Simon, H.A. (1976). Computer science as empirical inquiry: Symbols and search. Communications of the Association for Computing Machinery, 19(3), 113-126. (1975 ACM Turing Award Lecture.)
Simon, H.A. (1973). The structure of ill-structured problems. Artificial Intelligence, 4, 181-202.
Simon, H.A., & Siklossy, L. (Eds.) (1972). Representation and Meaning: Experiments with Information Processing Systems. Englewood Cliffs, NJ: Prentice-Hall.
Newell, A., & Simon, H.A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.
Baylor, G.W., & Simon, H.A. (1966). A chess mating combinations program. Proceedings of the 1966 Spring Joint Computer Conference, 28, 431-447.
Simon, H.A. (1963). Experiments with a heuristic compiler. Journal of the Association for Computing Machinery, 10, 493-506.
Newell, A., & Simon, H.A. (1961). GPS: A program that simulates human thought. In H. Billings (Ed.), Lernende automaten (pp. 109-124). Munchen: R. Oldenbourg.
Newell, A., Shaw, J.C., & Simon, H.A. (1958). Chess-playing programs and the problem of complexity. IBM Journal of Research and Development, 2, 320-335.
Newell, A., & Simon, H.A. (1956). The logic theory machine. IRE Transactions on Information Theory, IT-2(3), 61-79.