Intelligences ask questions

It has been suggested that the difference between animal intelligences and human level intelligence is that humans ask questions spontaneously. Many AI programs ask questions but what about the spontaneous asking of questions and what about learning to ask questions?
My AI Asa H learns by observing and copying behaviors that it sees.  It sees agents like myself ask questions.  Under similar circumstances Asa will then also ask questions.
Prairie dogs emit warning calls when they see evidence of a human nearby.  Similarly, at the lowest level of complexity a Lego NXT robot (either real or in simulation) may emit a beep whenever it detects a red ball.  A robot with an Asa H brain could see this and learn the same call. This easily occurs in simulation (though it would be difficult with Lego hardware).
In a multirobot experiment coordination of action may involve a robot asking for help (to push a heavy load for example). See, for example, Multirobot cooperation..., Kolling and Carpin, ICRA 2006, pg 1311.  The primitive call could be understood as a question; "Will you help?" Again, Asa H would learn to ask this same question when it encountered a similar situation.

Asa H natural language processing

I can now give Asa H a nearly 1000 word vocabulary. Enough for a telegraphic speech capability. These words are associated with concepts that are defined at various different levels in the Asa H hierarchical memory.

Categories

Ryle noted that good philosophical thinking required a good theory of categories.  Various philosophers in their arguments cite the category errors of their opponents.  But it is important to realize that the boundary of any given category is fuzzy and that categories evolve and change. (Just as all language evolves and changes.)  One of the things that I do in my experiments with Asa H is to follow how Asa's categories are formed and then evolve over time. (Watching thinking as it occurs in Asa's language of thought.) Running Asa H on a set of parallel computers the category activity is typically what is transmitted from one computer to the next, and from one level of the Asa H hierarchy to the next. (See my blog of 26 Aug. 2013 for an example of the simplest way this can be done.)

Do mathematical entities like numbers really exist?

Rather than Platonism (mathematical realism) I believe that numbers (and addition and subtraction and multiplication...) were developed by abstraction from earlier (physical) machinery that once existed in the real world.  Cockshott, et al, (Computation and its limits, Oxford Univ. Press, 2012) describe how this may have occurred on pages 11 through about 27. Some of my experiments with Asa H explore how abstractions are formed. It's easier to follow what's going on inside Asa than it is to understand the inner workings of a neural network program.  It's harder to follow what's going on inside Asa as compared to deductions in an expert system, however.

Higher order mathematical operations can then be composed out of addition, subtraction, and multiplication as is done with computers.

Scientism with values

I have argued in favor of a brand of scientism.  But, since I do not believe science is (or can be) value free, it is a scientism with a system of values.  (see my blogs of 20 Sept. 2013, 25 Oct. 2011 and 1 Sept. 2012)
This, as well as "scientific pluralism" (see my blogs of 8 Sept. 2011, 17 Aug. 2012 and "Changing what science is and how it's done", R. Jones, Trans. Kan. Acad. Sci., 116, 1/2, pg 78, 2013), counters some of the criticisms of the more traditional varieties of scientism. (see for example Scientism, Tom Sorell, Routledge, 1991)

Emotion, fear, reflex

A Lego NXT robot can be given an innate fear of heights using code like:

#define USONIC     IN_1
#define WHEELS    OUT_AC
.....
.....
#define CLIFF_DETECTED (SensorUS(USONIC)>35)
.....
.....
if (CLIFF_DETECTED)
{
   AvoidCliff();
}
.....
.....
sub AvoidCliff()
{
    Off(WHEELS);
    RotateMotorEx(WHEELS,80,550,-100,true,true);
    OffEx(WHEELS,RESET_ALL);
}

I have experimented with 5 mobile robots which were given a fear of heights in order to prevent them from falling down stairs or off of a tabletop.  Of course we can arrange for fear to be modulated by other cognitive processing.

Novelty detector/filter

In Asa H one or more similarity measures examines newly input spatial-temporal patterns and either adds them to existing clusters (cases) or records a new (novel) pattern (see blog of 10 Feb. 2011 and 14 May 2012 for code).