A computer model of simple forms of learning in infants
Pages 885 - 895
Abstract
Many workers have studied the problem of getting machines to exhibit aspects of intelligent behavior. It has become clear that a major limitation of the artificial intelligence field is the cost and difficulty of programming, which remains essentially a handicraft technique. What we need in artificial intelligence research are methods for the machine to be self-programming in a much deeper sense than the compilation process in use today. Briefly, we would like for the machine to "learn" to solve a problem, rather than being programmed in the usual laborious way. This report presents a computer program, using what I will call an "experience-driven compiler," which is able to program itself to solve a restricted class of problems involving cause-and-effect relationships. Although the program is not yet able to learn to solve problems of practical significance, it is hoped that the technique will be developed to the point where this can be done. I am in agreement with Turing's suggestion (1950) that the best way to achieve artificial intelligence is to find out what an infant has in his brain that allows him to become intelligent, put this capability into a computer, then allow the machine to "grow up" in much the same way as the baby does. (Of course, this is a statement of the problem rather than an explanation of how to solve it.) An additional purpose of the work is in psychology: we would like to have computer methods for testing theories of how learning might occur in living creatures.
References
[1]
R M Friedberg A learning machine, Part I IBM J Res and Dev Vol 2 pp 2--13 January 1958
[2]
P H Greene T L Ruggles Child and Spock IEEE Trans on Military Electronics Vol M17 No 2 and 3 April-July 1963
[3]
E R Guthrie The psychology of learning rev ed New York Harper 1952
[4]
D O Hebb The organization of behavior New York John Wiley and Sons Inc 1949
[5]
C Hewitt PLANNER: A language for proving theorems in robots Proc 1969 IJCAI pp 295--301
[6]
C L Hull A behavior system Yale University Press 1952
[7]
D Hume Enquiry concerning human understanding Oxford The Clarendon Press 1936
[8]
T L Jones A computer model of simple forms of learning MIT PhD thesis 1970
[9]
T L Jones The advice-taker as a means of symbolic computation MIT EE thesis 1966
[10]
I Kant Critique of pure reason Macmillan and Co Ltd 1934
[11]
J McCarthy Recursive functions of symbolic expressions Comm ACM Vol 3 April 1960
[12]
A Newell J C Shaw H A Simon Report on a general problem-solving program Proc Internatl Conf on Information Processing Paris UNESCO House 1959
[13]
J Piaget The origins of intelligence in children New York International Universities Press 1952
[14]
A L Samuel Some studies in machine learning using the game of checkers IBM J Res and Dev Vol 3 pp 211--219 July 1959
[15]
B F Skinner Science and human behavior New York Macmillan and Co 1953
[16]
J R Slagle An efficient algorithm for finding certain minimum-cost procedures for making binary decisions J ACM Vol 11 No 3 pp 253--254
[17]
A M Turing Computing machinery and intelligence in Computers and Thought pp 11--35 New York McGraw-Hill Book Company 1963
[18]
D A Waterman Generalization learning techniques for automating the learning of heuristics Artificial Intelligence Vol 1 Nos 1 and 2 Spring 1970
- A computer model of simple forms of learning in infants
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Published In
May 1972
1234 pages
ISBN:9781450379090
DOI:10.1145/1478873
Copyright © 1971 ACM.
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- AFIPS: American Federation of Information Processing Societies
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 November 1971
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