Twenty Years

A.s.a. H. has now become a twenty year long project (and still going).  

Hierarchical planning

Chaining of cases is possible on each level of A.s.a. H.'s hierarchical case-based memory.* This allows for hierarchical planning** at various orders of abstraction. On lower levels of the memory hierarchy this involves subsymbolic representations. On a higher level this can involve natural language.*** Reasoning can be sped up in this way.

* See, for example, Trans. Kansas Acad. Sci., vol. 109, no. 3/4, pg. 163-164, 2006.

** and deduction

*** or, alternatively, a mentalese

Hard to define concepts

 Even cognitive scientists are not in agreement about what constitutes things like consciousness. As we teach A.s.a. H. language we can see what conceptual structures the various words are labeling.* For example, we find, approximately:

conscious = (sense, think, health)

alive = (sense, act)

self = (sense, think, act, health)

where sense, think, act, and health are, in turn, defined roughly** as described in my blogs of 1 October 2015 and 21 July 2016.

* But one must recall that A.s.a. H. has a dynamic memory so individual memories/concepts can change somewhat as a result of new experiences. See my blog of 1 January 2023. 

** Different experiments have involved various robots having different sensors and servos, etc so these concepts can vary accordingly.

The importance of category formation

Yuan has emphasized the importance of category learning for artificial general intelligence and XAI.* A.s.a. H. employs just such a system.**

* Yang Yuan, A Categorical Framework of General Intelligence, arXiv:2303.04571v1, 8 March 2023.

** See, for example, R. Jones, Trans. Kansas Acad. Sci., Vol. 120, pg. 108, 2017 and my blogs of  1 Oct. 2015, 21 July 2016, 19 Oct. 2016, and 3 Aug. 2018.

Spacex Starship needs a launch abort system

 By launching the crew on Orion and rendezvousing with Starship in earth or lunar orbit one can sidestep the problem for now. But someone might be tasked with looking at ejector seats and things like the old M.O.O.S.E.* bail-out from orbit ideas.

* General Electric's Manned Orbital Operations Safety Equipment. See, for example, Teitel, Discover magazine, 12 Oct. 2017 or the wikipedia article on MOOSE.

Black boxes, explanations

 People typically can give brief, simple, explanations (reasons) for their beliefs and actions. These may, in fact, be an approximation to what is really a network of subconscious motivations. 

Sometimes A.s.a. H. takes an action or makes a decision that I don't expect/understand. When that occurs I usually try to explore the hierarchical patterns of activation that lead to this action/decision. I have found that frequently a number of weak activations may have "summed up" to produce the unexpected outcome. (Like when a large number of small weights in a neural network act together to produce some output signal.)

GPT-3, LaMDA, and ChatGPT

In my 28 January 2013 blog I pointed out that Siri did not have all of the functionality that I would want a machine intelligence to have.* Most importantly, it had no value system.** I would level the same criticisms of ChatGPT, GPT-3, and the like. Not to say that I don't find them interesting and useful.

* See, for example, my blog of 29 September 2010.

** I have argued that how intelligent a creature can be depends upon how good a value system it has. See for example my, Science Is Not Value Free, Trans. Kansas Acad. Sci., vol. 119, no. 2, pg. 249, 2016. One such value system is shown in my blog of 21 September 2010.