Robot dexterity

I am working to try to improve my robots' dexterity* by increasing the number of sensors and actuators (degrees of freedom) they employ. 

* and to encourage a richer definition of concepts

Mathematical cognition for AI

As a part of natural language understanding (and symbol grounding) work I have given A.s.a. H. preprocessors that recognize numerals and simple shapes.* I do not yet know what curriculum (training sequence) is needed in order to give A.s.a. the concepts required for a "natural mathematical understanding." Just how such mathematical cognition develops in humans is not well understood. 

* A.s.a. also has had builtin translation, rotation, reflection, scaling, logic functions, and similarity measures. Is there more that needs to be builtin (innate)?

Alternate realities

Some alternate realities are:

Materialism:  The entities described by physics are all that there is.

Idealism: Mind is all that there is.

Dualism: Materialism and spirit interacting with one another.

Theism: One (or more) supreme being and its creations.

Multiverse: Everett quantum mechanics, inflationary bubbles, fecund universe, etc.

It would be interesting to know what percentage of people have adopted each of these weltanschauung. The fragmentation of human society is quite natural, we experience some very different realities.

Differing concepts and meaning

The concepts A.s.a. H. learns* are defined** by their place in the hierarchically structured memory/case-base and the neighboring concepts they are linked with. This will vary a bit from one intelligent agent to another and one training history to another. I think this is also true among humans. This is one reason I don't find the definition of words to be as important as some philosophers do.

* and words which name them (see my blog of 5 November 2015)

** and meaning is established 

Specialist hardware agents

Most of the experiments that my A.s.a. H. robots have been tasked with* can be accomplished using a small set (society) of specialist agents**:

transporter, arm, various grippers, walker, flyer, swimmer, and brain

each with appropriate onboard sensors. 

* See, for example, my blog of 5 November 2015.

** See, also, my blogs of 1 and 16 February 2020.

Values

If an agent needs something he values it. Since a human's needs* differ from those of an AI humans and AIs will have different values. This may likely lead to some conflict between humans and AIs.

* humans need air, water, food, mates, etc. (The problem with money, scalar utility, is it is one dimensional while the world is not.)

Mental time travel

 A.s.a. H. decomposes its model of the world into concepts and sequences (transition models over the vector state space). In the version of  A.s.a. H. 2.0 light published in my 10 February 2011 blog utility controlled extrapolations can occur around line 3000 of the code. Other learning/extrapolation algorithms have been discussed in various of my publications on A.s.a. H.* With these algorithms A.s.a. rethinks the past and past actions on multiple levels of abstraction over its hierarchical memory trying to improve the expected rewards/utility. Responses to alternative possible environmental conditions are also explored/evaluated. i.e., mental time travel, another piece of machine consciousness.

* See, for example, Trans. Kansas Academy of Science, vol. 109, no. 3-4, pg 159-167, 2006 and vol. 124, no. 1-2 , pg 146, 2021 as well as work with A.s.a. F.