Technology
Statistical models for recognition and recall of stimulus patterns by human observers
In Yovitts, M. and Cameron, S. (eds.) Self-organizing Systems. New York: Pergamon
A paradox regained
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An improved proof procedure
This work is partly included in a project sponsored by Statens tekniska forskningsråd (Sweden). Berg, and Mr Voghera for reading the manuscript and making valuable suggestions (see also n. 11). Use the link below to share a full-text version of this article with your friends and colleagues.
Experimental study of "hypothesis formation" by computer
Research report RC 294, IBM, Yorktown Heights, New York
Pattern recognition with an adaptive network
IRE International Convention Record, pt 2, pp. 66-70
On the convergence of reinforcement procedures in simple perceptrons
Report VG-1196-G-4, Cornell Aeronautical Laboratory.
A computing procedure for quantification theory
The hope that mathematical methods employed in the investigation of formal logic would lead to purely computational methods for obtaining mathematical theorems goes back to Leibniz and has been revived by Peano around the turn of the century and by Hilbert's school in the 1920's. Hilbert, noting that all of classical mathematics could be formalized within quantification theory, declared that the problem of finding an algorithm for determining whether or not a given formula of quantification theory is valid was the central problem of mathematical logic. And indeed, at one time it seemed as if investigations of this "decision" problem were on the verge of success. However, it was shown by Church and by Turing that such an algorithm can not exist. This result led to considerable pessimism regarding the possibility of using modern digital computers in deciding significant mathematical questions.
An approach to automatic theory formation
In von Foerster, H. (ed) Illinois Symposium on Principles of Self-Organization, Univ. of Illinois, Urbana, IL (1960)