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From: honavar@speedy.WISC.EDU (A Buggy AI Program)
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Subject: Tech. report abstract
Message-ID: <4472@spool.wisc.edu>
Date: Thu, 15-Oct-87 14:22:16 EDT
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Posted: Thu Oct 15 14:22:16 1987
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Computer Sciences Technical Report #717, September 1987.
--------------------------------------------------------


       RECOGNITION CONES: A NEURONAL ARCHITECTURE FOR
                  PERCEPTION AND LEARNING


                Vasant Honavar, Leonard Uhr

                Computer Sciences Department
              University of Wisconsin-Madison
                 Madison, WI 53706. U.S.A.


			ABSTRACT

          There is currently a great deal  of  interest
     and  activity  in  developing  connectionist, neu-
     ronal,  brain-like  models,  in  both   Artificial
     Intelligence  and  Cognitive  Science.  This paper
     specifies  the  main  features  of  such  systems,
     argues  for the need for, and usefulness of struc-
     turing networks of neuron-like units into  succes-
     sively  larger  brain-like  modules,  and examines
     "recognition cone" models of perception from  this
     perspective,   as  examples  of  such  structures.
     Issues addressed include architecture, information
     flow,  and the parallel-distributed nature of pro-
     cessing and  control  in  recognition  cones;  and
     their use in perception and learning.


-----
Vasant Honavar
honavar@speedy.wisc.edu