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From: ian@shire (Ian Parberry)
Newsgroups: comp.ai.neural-nets
Subject: Re: Probabilistic Logic Nodes  (PLN)
Keywords: neural networks and complexity theory
Message-ID: <4290@psuvax1.cs.psu.edu>
Date: 13 Feb 89 16:37:26 GMT
References: <1799@cps3xx.UUCP>
Sender: news@psuvax1.cs.psu.edu
Reply-To: ian@psuvax1 (Ian Parberry)
Organization: Penn State University
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In <1799@cps3xx.UUCP> artzi@cpsvax.cps.msu.edu (Ytshak Artzi-CPS) writes:
>
>    1. Is there any research being made on the relationship between
>        Neural Nets and Probabilistic Automata ?

As far as computation with probabilistic neural networks goes (as opposed
to learning), some elementary observations have been made in:

Parberry and Schnitger, "Relating Boltzmann Machines to Conventional
Models of Computation'', Neural Networks, Vol. 2., pp. 59-79, 1989.

I don't know whether the details carry over to your model, but you
might want to check it out.  For some background on the relationship
between complexity theory (for those unfamiliar with the term, it can
be viewed as an outgrowth of automata theory concerned with resource-
bounded computation) and neural networks you might want to consult:

Parberry and Schnitger, "Parallel Computation with Threshold Functions",
Journal of Computer and System Sciences, Vol. 36, No. 3, 1988.

Parberry, "A Primer on the Complexity Theory of Neural Networks",
in "A Sourcebook on Formal Techniques in Artificial Intelligence",
R. B. Banerji (Ed.), Elsevier, To Appear in 1989 (hopefully).

I apologize for appearing to have written a commercial for myself.
All of the references on the subject known to me are mentioned in
my articles above.  Call by reference is more efficient than call by
value.  :-)
-------------------------------------------------------------------------------
			Ian Parberry
  "The bureaucracy is expanding to meet the needs of an expanding bureaucracy"
  ian@psuvax1.cs.psu.edu  ian@psuvax1.BITNET  ian@psuvax1.UUCP  (814) 863-3600
 Dept of Comp Sci, 333 Whitmore Lab, Penn State Univ, University Park, Pa 16802