ONT Jets & Sharks in RefLog
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I am going to store this somewhat dated, but still
archly typical example here for the sake of future
reference, if not yet exactly to claim "reverence".
Jon Awbrey
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Excerpt from "Theme One: A Program of Inquiry",
By Jon Awbrey and Susan Awbrey, August 9, 1989.
| Historical Note
|
| The term "boundary operator" is the old name
| for a logical bracket of the form "(_,...,_)",
| the text frame that parses into a "cactus lobe":
|
| o-...-o
| \ /
| \ /
| @
|
| The name "Study" refers to the module of the Theme One Program
| that functioned as the propositional calculus managing utility.
Example 5. Jets and Sharks
The propositional calculus based on the boundary operator
can be interpreted in a way that resembles the logic of
activation states and competition constraints in certain
neural network models. One way to do this is by interpreting
the blank or unmarked state as the resting state of a neural
pool, the bound or marked state as its activated state, and
by representing a mutually inhibitory pool of neurons A, B, C
in the expression "(A, B, C)". To illustrate this possibility,
we transcribe a well-known example from the parallel distributed
processing literature [McR] and work through two of the associated
exercises as portrayed in Existential Graph format.
o----------------------------------------------------------------------
|
| (( art ),( al ),( sam ),( clyde ),( mike ),
| ( jim ),( greg ),( john ),( doug ),( lance ),
| ( george ),( pete ),( fred ),( gene ),( ralph ),
| ( phil ),( ike ),( nick ),( don ),( ned ),( karl ),
| ( ken ),( earl ),( rick ),( ol ),( neal ),( dave ))
|
| ( jets , sharks )
|
| ( jets ,
| ( art ),( al ),( sam ),( clyde ),( mike ),
| ( jim ),( greg ),( john ),( doug ),( lance ),
| ( george ),( pete ),( fred ),( gene ),( ralph ))
|
| ( sharks ,
| ( phil ),( ike ),( nick ),( don ),( ned ),( karl ),
| ( ken ),( earl ),( rick ),( ol ),( neal ),( dave ))
|
| (( 20's ),( 30's ),( 40's ))
|
| ( 20's ,
| ( sam ),( jim ),( greg ),( john ),( lance ),
| ( george ),( pete ),( fred ),( gene ),( ken ))
|
| ( 30's ,
| ( al ),( mike ),( doug ),( ralph ),( phil ),( ike ),
| ( nick ),( don ),( ned ),( rick ),( ol ),( neal ),( dave ))
|
| ( 40's ,
| ( art ),( clyde ),( karl ),( earl ))
|
| (( junior_high ),( high_school ),( college ))
|
| ( junior_high ,
| ( art ),( al ),( clyde ),( mike ),( jim ),
| ( john ),( lance ),( george ),( ralph ),( ike ))
|
| ( high_school ,
| ( greg ),( doug ),( pete ),( fred ),( nick ),
| ( karl ),( ken ),( earl ),( rick ),( neal ),( dave ))
|
| ( college ,
| ( sam ),( gene ),( phil ),( don ),( ned ),( ol ))
|
| (( single ),( married ),( divorced ))
|
| ( single ,
| ( art ),( sam ),( clyde ),( mike ),( doug ),( pete ),
| ( fred ),( gene ),( ralph ),( ike ),( nick ),( ken ),( neal ))
|
| ( married ,
| ( al ),( greg ),( john ),( lance ),( phil ),
| ( don ),( ned ),( karl ),( earl ),( ol ))
|
| ( divorced ,
| ( jim ),( george ),( rick ),( dave ))
|
| (( bookie ),( burglar ),( pusher ))
|
| ( bookie ,
| ( sam ),( clyde ),( mike ),( doug ),
| ( pete ),( ike ),( ned ),( karl ),( neal ))
|
| ( burglar ,
| ( al ),( jim ),( john ),( lance ),
| ( george ),( don ),( ken ),( earl ),( rick ))
|
| ( pusher ,
| ( art ),( greg ),( fred ),( gene ),
| ( ralph ),( phil ),( nick ),( ol ),( dave ))
|
o----------------------------------------------------------------------
We now apply Study to the proposition
defining the Jets and Sharks data base.
With a query on the name "ken" we obtain the following
output, giving all the features associated with Ken:
o----------------------------------------------------------------------
|
| ken
| sharks
| 20's
| high_school
| single
| burglar
|
o----------------------------------------------------------------------
With a query on the two features "college" and "sharks" we obtain
the following outline of all features satisfying these constraints:
o----------------------------------------------------------------------
|
| college
| sharks
| 30's
| married
| bookie
| ned
| burglar
| don
| pusher
| phil
| ol
|
o----------------------------------------------------------------------
From this we discover that all college sharks are 30-something and married.
Further, we have a complete listing of their names broken down by occupation,
as no doubt all of them will be, eventually.
| Reference:
|
| McClelland, James L. & Rumelhart, David E.,
|'Explorations in Parallel Distributed Processing:
| A Handbook of Models, Programs, and Exercises',
| MIT Press, Cambridge, MA, 1988.
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