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Proceedings Paper

A Pulse-Driven Learning Network
Author(s): W. E. Simon; W. S. Cook; J. R. Carter; D.A. J. Outteridge
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Paper Abstract

A pulse-driven learning network can be applied to any problem where adaptive behavior (i.e., the ability to adjust behavior to situations where a priori solutions are not known) is important. The pulse-driven learning network approach is different from other connectionist techniques in the way communication occurs between nodes. Since other connectionist techniques allow communication to occur in a continuum fashion, solutions at each compute cycle exist only when the system is in an equilibrium state. Not only is this a very computationally intensive process, but false solutions are also possible. The learning network does not have either of these problems because communication between nodes is in the form of a pulse and the correction solution is extracted from the network in as few as ten pulses from the input nodes. The results presented herein demonstrate the ability of a pulse-driven learning network to exhibit learning from association, learning from reward/punishment for simple problems and the existence of a stable solution for solving a complex problem.

Paper Details

Date Published: 27 March 1987
PDF: 8 pages
Proc. SPIE 0726, Intelligent Robots and Computer Vision V, (27 March 1987);
Show Author Affiliations
W. E. Simon, Martin Marietta Denver Aerospace (United States)
W. S. Cook, Martin Marietta Denver Aerospace (United States)
J. R. Carter, Martin Marietta Denver Aerospace (United States)
D.A. J. Outteridge, Martin Marietta Denver Aerospace (United States)

Published in SPIE Proceedings Vol. 0726:
Intelligent Robots and Computer Vision V
David P. Casasent, Editor(s)

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