Specialization of the environment

 Streets and roads are the segment of the environment where transportation is concentrated. Factories are the segment of the environment where manufacturing occurs. Farms are the segment where food is grown. etc. etc. etc.... Highways can be automated* just as factories are. Each segment of the environment can be specialized and automated too. Specialist agents would then operate in specialized environments.** (Someone can write a dystopian novel about a curious little forklift robot who escapes the confines of his factory for the freedom of the open road with the f.s.d. truck he met on the loading dock.)

* See my blog of 20 June 2025.

** I would have no idea of how to work on a farm and a farmer would have no idea of what to do in a physics laboratory.

Sentience is not consciousness

The standard dictionary definition of sentience "is the ability to feel or sense" including things like pain. By this definition every robot I have is sentient. A more detailed and scientific definition for sentience is Austin Clark's A Theory of Sentience*, Oxford University Press, 2000. A definition of consciousness is much more problematic. Blackboards and spreading activation are common models of artificially conscious systems.

* Which proves to be a good description of sentience in my A.s.a. H. robots.

Primitive concept development

 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.

A.s.a. H. Blackboards

 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.