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[Ron Sun]

Paper announcement:
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                    Beyond Associative Memories:
             Logics and Variables in Connectionist Models 


                             Ron Sun
                         Honeywell SSDC
                      3660 Technology Drive
                      Minneapolis, MN 55418





                            abstract

This paper demonstrates the role of connectionist (neural network) 
models in reasoning beyond that of an associative memory.
First we show that there is a connection between propositional logics
and the weighted-sum computation customarily used in connectionist models.
Specifically, the weighted-sum computation can handle Horn clause logic 
and Shoham's logic as special cases. Secondly, we show how variables 
can be incorporated into connectionist models to enhance their 
representational power.  We devise solutions to the connectionist 
variable binding problem to enable connectioninst networks to handle 
variables and dynamic bindings in reasoning.  A new model, the  Discrete 
Neuron formalism, is employed for dealing with the variable binding 
problem, which is an extension of the weighted-sum models.
Formal definitions are presented, and examples are analyzed in details.


    To appear in: Information Sciences,  
        special issues on neural nets and AI



It is FTPable from archive.cis.ohio-state.edu
  in: pub/neuroprose
No hardcopy available.


FTP procedure:
        unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
        Name: anonymous
        Password: neuron
        ftp> cd pub/neuroprose
        ftp> binary
        ftp> get sun.beyond.ps.Z
        ftp> quit
        unix> uncompress sun.beyond.ps.Z
        unix> lpr sun.beyond.ps (or however you print postscript)