Toward memory-based reasoning

Communications of the ACM

Volumn 29, Issue 12, 1986, Pages 1213-1228

  Stanfill, Craig ^a   Waltz, David ^a  

^a SUN MICROSYSTEMS   (United States)

Author keywords

Connection Machine; massively parallel architectures; memory

Indexed keywords

COMPUTER SYSTEMS, DIGITAL - PARALLEL PROCESSING;

CONNECTION MACHINE; MEMORY-BASED REASONING;

ARTIFICIAL INTELLIGENCE;

EID: 0022909661     PISSN: 00010782     EISSN: 15577317     Source Type: Journal    
DOI: 10.1145/7902.7906     Document Type: Article

References (47)

1. Alterman, R. Issues in adaptive planning. Rep. UCB/CSD 87/304, Computer Science Division, Univ. of California at Berkeley, July 1986.
2. Charniak, E. The Bayesian basis of common sense medical diagnosis. In Proceedings of the 3rd National Conference on Artificial Intelligence (AAA1-83) (Washington, D.C., Aug. 22-26). American Association for Artificial Intelligence, Menlo Park, Calif., 1983, pp. 70–73.
3. Cheeseman, P. A method for computing Bayesian probability values for expert systems. In Proceedings of the 8th International Joint Conference on Artificial Intelligence (Karlsruhe, West Germany, Aug. 8-12). 1983, pp. 198–202.
4. DeJong, G., and Mooney, R. Explanation-based learning: An alternative view. Mach. Learn. 1, 2 (Apr. 1986), 145–176.
5. Dreyfus, H., and Dreyfus, S. Why computers may never think like people. Technol. Rev. 89, 1 (Jan. 1986), 42–61.
6. Fahlman, S.E. NETL: A System for Representing and Using Real-World Knowledge. MIT Press, Cambridge, Mass., 1979.
7. Feldman, I.A. Introduction to the special issue on connectionism. Cognitive Sci. 9, 1 (Jan.-Mar. 1985), 1–169.
8. Feldman, J.A., and Ballard, D.H. Connectionist models and their properties. Cognitive Sci. 6, 3 (July-Sept. 1982), 205–254.
9. Gelerntner, H. Realization of a geometry theorem proving machine. In Computers and Thought, E.A. Feigenbaum and J. Feldman, Eds. McGraw-Hill, New York. 1963.
10. Hewitt, C. Description and theoretical analysis of PLANNER. Doctoral dissertation, Dept. of Mathematics, MIT, Cambridge, Mass., 1972.
11. Hillis, D. The Connection Machine. MIT Press, Cambridge, Mass., 1985.
12. Hillis, W.D., and Steel, G.L., Jr. Data parallel algorithms. Commun. ACM 29, 12 (Dec. 1986).
13. Hinton, G., and Anderson, J., Eds. Parallel Models of Associative Memory. Lawrence Erlbaum Associates, Hillsdale, N.J., 1981.
14. Holland, J. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, Mich., 1975.
15. Hopfield, J.J. Neural networks and physical systems with emergent collective computational abilities. Proc. Natl. Acad. Sci. 79 (1982), 2554–2558.
16. Kanerva, P. Self-propagating search: A unified theory of memory. Rep. CSLI-84-7, Center for the Study of Language and Information, Stanford University, Calif., Mar. 1984.
17. Kolodner, J. Retrieval and Organizational Strategies in Conceptual Memory: A Computer Model. Lawrence Erlbaum Associates, Hillsdale, N.J., 1984.
18. Kowalski, R.A. Predicate logic as programming language. In Proceedings of the IFIPS Congress (Amsterdam). International Federation of Information Processing Societies, 1974, pp. 570–574.
19. Lebowitz, M. Integrated learning: Controlling explanation. Cognitive Sci. 10, 2 (Apr.-June 1986), 219–240.
20. Lebowitz, M. Not the path to perdition: The utility of similarity-based learning. In Proceedings of the 5th National Conference on Artificial Intelligence (AAAI-86) (Philadelphia, Pa., Aug. 11-15). American Association for Artificial Intelligence, Menlo Park, Calif., 1986, pp. 533–537.
21. Lee, W. Decision Theory and Human Behavior. Wiley, New York, 1971.
22. McClelland, J.L., and Rumelhart, D.E., Eds. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press, Cambridge, Mass., 1986.
23. Merriam-Webster's Pocket Dictionary. Merriam-Webster, Springfield, Mass., 1974.
24. Michalski, R., Carbonell, J., and Mitchell, T., Eds. Machine Learning. Tioga, Palo Alto, Calif., 1983.
25. Michalski, R., Carbonell, J., and Mitchell, T., Eds. Machine Learning. Vol. 2, Tioga, Palo Alto, Calif., 1986.
26. Miller, G.A., Gelenter, E., and Pribram, K. Plans and the Structure of Behavior. Holt, Rinehart and Winston, New York, 1960.
27. Minsky, M. The Society of Minds. Simon and Schuster. New York: To be published.
28. Mitchell, T., Utgoff, P., and Banerji, R. Learning by experimentation: Acquiring and refining problem-solving heuristics. In Machine Learning, R. Michalski et. al., Eds. Tioga, Palo Alto, Calif., 1983.
29. Mooney, R. A domain independent explanation-based generalizer. In Proceedings of the 5th National Conference on Artificial Intelligence (AAAI-86) (Philadelphia, Pa., Aug. 11-15). American Association for Artificial Intelligence, Menlo Park, Calif., 1986, pp. 551–555.
30. Newell, A. The knowledge level. Al Mag. 2, 2 (Summer 1981), 1–20.
31. Newell, A., and Simon, H. Human Problem Solving. Prentice-Hall, Engelwood Cliffs, N.J., 1972.
32. Newell, A., and Simon, H.A. GPS, a program that simulates human thought. In Computers and Thought, E.A. Feigenbaum and J. Feldman, Eds. McGraw-Hill, New York, 1963, pp. 279–293.
33. Newell, A., Ernst, G., and Shaw, J. Elements of a theory of human problem solving. Psychol. Rev. 65, (1958), 151–166.
34. Quinlan, J.R. Discovering rules from large collections of examples: A case study. In Expert Systems in the Micro Electronic Age, D. Michie, Ed. Edinburgh University Press, Edinburgh, 1979.
35. Robinson, J.A. A machine-oriented logic based on the resolution principle. J. ACM 12, 1 (Jan. 1965), 23–41.
36. Rosenblatt, F. Principles of Neurodynamics: Perceptions and Theory of Brain Mechanisms. Spartan, Washington, D.C., 1961.
37. Rumelhart, D.E., Hinton, G.E., and Williams, R.J. Learning internal representations by error propagation. In Parallel Distributed Processing: Explorations in the Microstructure of Cognition, J.L. McClelland and D.E. Rumelhart, Eds. MIT Press, Cambridge, Mass., 1986.
38. Samuel, A. Some studies in machine learning using the game of checkers. IBM J. Res. Dev. 3, 3 (1959). 210–299.
39. Samuel, A. Some studies in machine learning using the game of checkers II. IBM J. Res. Dev. 13, 6 (1967), 601–617.
40. Schank, R.C., Dynamic Memory: A Theory of Reminding and Learning in Computers and People. Cambridge University Press, New York, 1982.
41. Sejnowski, T.J., and Rosenberg, C.R. NETtalk: A parallel network that learns to read aloud. Electrical Engineering and Computer Science Dept., Johns Hopkins Univ. Tech. Rep. JHU/EECS-86/01, 1986.
42. Shortliffe, E. Computer Based Medical Consultations: MYCIN. Elsevier North-Holland, New York, 1976.
43. Stanfill, C., and Kahle, B. Parallel free-text search on the Connection Machine system. Commun. ACM 29, 12 (Dec. 1986), 1229–1239.
44. Sussman, G., Winograd, T., and Charniak, E. MICRO-PLANNER reference manual. Al Memo 203a, MIT Al Laboratory, MIT, Cambridge, Mass., Dec. 1971.
45. Waltz, D.L., Genesereth, M., Hart, P., Hendrix, G., Joshi, A., McDermott, J., Mitchell, T., Nilsson, N., Wilensky, R., and Woods, W. Artificial intelligence: An assessment of the state-of-the-art and recommendation for future directions. Al Mag. 4, 3 (Fall 1983), 55–67.
46. Winston, P. Learning structural descriptions from examples. In The Psychology of Computer Vision, P. Winston, Ed. McGraw-Hill, New York, 1975.
47. Woods, W.A. Transition network grammars for natural-language analysis. Commun. ACM 13, 10 (Oct. 1970), 591–606.