Even light versions of A.s.a. H.* are designed to handle temporal patterns/cases. But as A.s.a. learns Wierzbicka's "alphabet of human thought" the early concepts do not involve a function of time. Concepts involving temporal patterns develop later.** I believe human concept formation follows a similar pattern.
* See, for example, my blog of 10 February 2011.
** The concept structure in my 4 September 2024 blog include a few.
My earliest A.s.a. H. software was feedforward and had the output of each classifier layer feeding directly into the next higher layer.* More generally it is possible to employ (one or more) blackboards. In that case external inputs** are sent to the blackboard as are the activated outputs of all the various classifier layers. The classifier layers all watch the blackboard for input.*** This allows for feedback from "higher" layers to "lower" ones. Weights can be applied to all inputs to the blackboard in order to adjust how much feedback is present, to favor input from adjacent layers, etc.
* R. Jones, Trans. Kansas Acad. Sci., vol. 109, pg. 159, 2006 and W. Ertel, Intro. to Artificial Intelligence, Springer, 2017(2nd edition), pg. 278 and the last paragraph of page 280.
** Perhaps after preprocessing.
*** See my blog of 6 October 2024.
