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From: jam@bu-cs.BU.EDU (Jonathan Marshall)
Newsgroups: net.ai
Subject: Re: simulating a neural network
Message-ID: <2001@bucsd.bu-cs.BU.EDU>
Date: Mon, 20-Oct-86 14:25:50 EDT
Article-I.D.: bucsd.2001
Posted: Mon Oct 20 14:25:50 1986
Date-Received: Tue, 21-Oct-86 23:34:00 EDT
References: <223@eneevax.UUCP>
Reply-To: jam@bucsd.UUCP (Jonathan Marshall)
Distribution: net
Organization: Boston Univ. CS Dept.
Lines: 83
Keywords: neural networks, simulations
Summary: A lot of work has already been done on this subject.

In article <223@eneevax.UUCP> iarocci@eneevax.UUCP (Bill Dorsey) writes:
>
>   Having recently read several interesting articles on the functioning of
>neurons within the brain, I thought it might be educational to write a program
>to simulate their functioning.  Being somewhat of a newcomer to the field of
>artificial intelligence, my approach may be all wrong, but if it is, I'd
>certainly like to know how and why.
>   The program simulates a network of 1000 neurons.  Any more than 1000 slows
>the machine down excessively.  Each neuron is connected to about 10 other
>neurons.
>  .
>  .
>  .
>   The initial results have been interesting, but indicate that more work
>needs to be done.  The neuron network indeed shows continuous activity, with
>neurons changing state regularly (but not periodically).  The robot (!) moves
>around the screen generally winding up in a corner somewhere where it occas-
>ionally wanders a short distance away before returning.
>   I'm curious if anyone can think of a way for me to produce positive and
>negative feedback instead of just feedback.  An analogy would be pleasure
>versus pain in humans.  What I'd like to do is provide negative feedback
>when the robot hits a wall, and positive feedback when it doesn't.  I'm 
>hoping that the robot will eventually 'learn' to roam around the maze with-
>out hitting any of the walls (i.e. learn to use its senses).
>   I'm sure there are more conventional ai programs which can accomplish this
>same task, but my purpose here is to try to successfully simulate a network
>of neurons and see if it can be applied to solve simple problems involving
>learning/intelligence.  If anyone has any other ideas for which I may test
>it, I'd be happy to hear from you.


Here is a reposting of some references from several months ago.
* For beginners, I especially recommend the articles marked with an asterisk.

Stephen Grossberg has been publishing on neural networks for 20 years.
He pays special attention to designing adaptive neural networks that
are self-organizing and mathematically stable.  Some good recent
references are:

 (Category Learning):----------
*  G.A. Carpenter and S. Grossberg, "A Massively Parallel Architecture for
     a Self-Organizing Neural Patttern Recognition Machine."  Computer
     Vision, Graphics, and Image Processing.  In Press.
   G.A. Carpenter and S. Grossberg, "Neural Dynamics of Category Learning
     and Recognition: Structural Invariants, Reinforcement, and Evoked
     Potentials."  In M.L. Commons, S.M. Kosslyn, and R.J. Herrnstein (Eds),
     Pattern Recognition in Animals, People, and Machines.  Hillsdale, NJ:
     Erlbaum, 1986.
 (Learning):-------------------
*  S. Grossberg, "How Does a Brain Build a Cognitive Code?"  Psychological
     Review, 1980 (87), p.1-51.
*  S. Grossberg, "Processing of Expected and Unexpected Events During
     Conditioning and Attention."  Psychological Review, 1982 (89), p.529-572.
   S. Grossberg, Studies of Mind and Brain: Neural Principles of Learning,
     Perception, Development, Cognition, and Motor Control.  Boston:
     Reidel Press, 1982.
   S. Grossberg, "Adaptive Pattern Classification and Universal Recoding:
     I. Parallel Development and Coding of Neural Feature Detectors."
     Biological Cybernetics, 1976 (23), p.121-134.
   S. Grossberg, The Adaptive Brain: I. Learning, Reinforcement, Motivation,
     and Rhythm.  Amsterdam: North Holland, 1986.
*  M.A. Cohen and S. Grossberg, "Masking Fields: A Massively Parallel Neural
     Architecture for Learning, Recognizing, and Predicting Multiple
     Groupings of Patterned Data."  Applied Optics, In press, 1986.
(Vision):---------------------
   S. Grossberg, The Adaptive Brain: II. Vision, Speech, Language, and Motor
     Control.  Amsterdam: North Holland, 1986.
   S. Grossberg and E. Mingolla, "Neural Dynamics of Perceptual Grouping:
     Textures, Boundaries, and Emergent Segmentations."  Perception &
     Psychophysics, 1985 (38), p.141-171.
   S. Grossberg and E. Mingolla, "Neural Dynamics of Form Perception:
     Boundary Completion, Illusory Figures, and Neon Color Spreading."
     Psychological Review, 1985 (92), 173-211.
(Motor Control):---------------
   S. Grossberg and M. Kuperstein, Neural Dynamics of Adaptive Sensory-
     Motor Control: Ballistic Eye Movements.  Amsterdam: North-Holland, 1985.


If anyone's interested, I can supply more references.

--Jonathan Marshall

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