Learning in Memory Technical Report

[Simon Dennis]

The following technical report is available for anonymous ftp.


TITLE: Integrating Learning into Models of Human Memory: 
	The Hebbian Recurrent Network

AUTHORS: Simon Dennis and Janet Wiles

ABSTRACT: 

We develop an interactive model of human memory called the Hebbian
Recurrent Network (HRN) which integrates work in the mathematical
modeling of memory with that in error correcting connectionist
networks.  It incorporates the matrix model (Pike, 1984; Humphreys,
Bain & Pike, 1989) into the Simple Recurrent Network (SRN, Elman,
1989).  The result is an architecture which has the desirable memory
characteristics of the matrix model such as low interference and
massive generalization but which is able to learn appropriate encodings
for items, decision criteria and the control functions of memory which
have traditionally been chosen a priori in the mathematical memory
literature.  Simulations demonstrate that the HRN is well suited to a
recognition task inspired by typical memory paradigms.  When compared
against the SRN the HRN is able to learn longer lists, generalizes from
smaller training sets, and is not degraded significantly by increasing
the vocabulary size.


Please mail correspondence to mav at cs.uq.oz.au

Ftp Instructions:


$ ftp exstream.cs.uq.oz.au
Connected to exstream.cs.uq.oz.au.
220 exstream FTP server (Version 6.12 Fri May 8 16:33:17 EST 1992) ready.
Name (exstream.cs.uq.oz.au:mav): anonymous
331 Guest login ok, send e-mail address as password.
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ftp> cd pub/TECHREPORTS/department
250 CWD command successful.
ftp> bin
200 Type set to I.
ftp> get TR0252.ps.Z
200 PORT command successful.
150 Opening BINARY mode data connection for TR0252.ps.Z (160706 bytes).
226 Transfer complete.
local: TR0252.ps.Z remote: TR0252.ps.Z
160706 bytes received in 0.71 seconds (2.2e+02 Kbytes/s)
ftp> quit
221 Goodbye.
$ 

Printing Instructions:

$ zcat TR0252.ps.Z | lpr