(you may click the number of the subfile to be viewed, or scroll down)

This file contains the following subfiles:

20 - tonal inflection
21 - word prediction example
21.5 - search efficiency


(subfile 20: tonal inflection

Clearly, four different replies are required for the four versions of the following sentence:

1) I want to go home. (George doesn't want to, though.)

2) I WANT to go home. (It is [only]my wish. It is not an urgent need.)

3) I want to GO home. (I wish to travel to my dwelling.  The travel itself is what's important.)

4) I want to go HOME. (As opposed to going to work.)

Tonal inflection of this type can become visible to the algorithm by defining a two-value axis for "inflection" and allowing the input stage to include the assignment of accented words. The context-specific (temporary) parts of the words' definitions include values on this axis – values that are never saved to the “dictionary” database. Storing inflections from input will of course result in the output of inflection as well.

(A discussion of tonal emphasis also requires "bombs" and "transforms", which see.) Suppose some input has arrived which begins “Do you like....” and in which tonal emphasis is placed on “you”. Many subsequent replies would have begun “I (do) like....”. Thus an element of one type of transform would look just like a bomb from “you” to “I”. Another fuzzy explosion of possibilities is available without any computational strain, with different variants being appropriate to different tonal stresses in the input:

             I                         George                          You

          like                       dislikes                   used to hate

        apples                     pears                        bananas

       period              question mark                  comma


(subfile 21: Predicting the existence of  words not yet seen by the program)

Suppose training conversations have been limited to food and eating. "Listening to conversations" requires that a number of relevant words be defined; after defining words for the subject "eating", there would be a number of them that might differ along only one axis (these words represent the types of apples). This situation would allow the creation a particular type of template: most spans are rather limited, because nearly identical and specific values are present in all the words' definitions (all fruits are 1. material objects 2. of moderate size 3. subject to being eaten etc.), but one span, on one axis, would be very wide, because the various words in the collection have very different values for that parameter (apples come in several colors). The program is then in a position to search for a class-defining word in meaning space, and to ask about it, if there is nothing at the location specified. In this way our deaf and dumb computer could come to realize, on its own, that a class-word for this set of objects might exist.



(subfile 21.5: Recording and advance-preparation of searches)

Suppose the program has been sent to a point in MS and finds no object there. A painfully slow and inefficient search must be undertaken to find the closest object. As the search progresses, a list of points "checked" is kept, and when an object is found, pointers to that object are inserted at each MS point traversed during the search. Thus one need never repeat the same search.

Clearly collisions will arise when new objects are inserted; that is, pointers that were inserted before the new object might no longer point to the closest object, which could now be the new object. Fortunately the program can always tell which of two possible pointers should be kept, since distances can easily be calculated and the shorter pointer discovered. In fact, both may be kept just as easily, at the cost of more memory, if their dates are recorded.