Hierarchical STM

Asa H's short term memory (STM) is distributed across the various levels in Asa's hierarchical memory, unlike the typically monolithic STM that is assumed in most simple cognitive models. (See my blog of  5 March 2015.)

Work on machine consciousness

Hobson decomposes consciousness into 10 functional components which he briefly defines:
( in Scientific Approaches to Consciousness, Cohen and Schooler, Psychology Press, 1996, page 383 )

Attention:                Selection of input data
Perception:              Representation of input data
Memory:                 Retrieval of stored representations
Orientation:            Representation of time, place, and person
Thought:                 Reflection upon representation
Narrative:               Linguistic symbolization of representations
Emotion:                Feelings about representations
Instinct:                  Innate propensities to act
Intention:               Representations of goals
Volition:                Decisions to act

My artificial intelligence Asa H performs all of these functions, some more completely than others.

Attention:               See blogs of 1 June 2011, 21 June 2014, 15 October 2015 for
                               example.
Perception:             This works well though we would like to have more input sensors.
Memory:                Our case vector memory works well.
Orientation:            Time is represented explicitly. Our self model can represent a person.
                                Asa can recognize where it is by its surroundings.
Thought:                 Extrapolation and other learning algorithms examine and operate on
                               the case memories.
Narrative:               Asa has a simple natural language vocabulary but this is primitive
                               compared to that used by most humans.
Emotion:                Asa has a pain circuit and an advanced value system.  It does not
                               share all of our human emotions.
Instinct:                  Asa can have pain and reflexes, a drive to reproduce, etc.
Intention:               Asa's value system defines its goals.
Volition:                Asa acts so as to optimize its vector utility.

I believe that Asa is more conscious than humans in some ways* and less conscious in others.

* in that it has access to and control over some of its internal processes which humans don't.
Asa also has a much larger STM (short term memory) capacity.

Scientific pluralism, multiple realities, and teaching

The average student wants to learn about the one correct truth/reality.  When I'm asked any given question multiple, maybe conflicting, lines of thought/argument pop into my consciousness.  Sometimes I can hold back all the detail.  Usually I can not.

Meccano again

To make Lego stronger and more rigid they recommend adding more bricks.  You can also use glue but then you can't modify the machine.  Meccano, be it plastic or metal, is held together with screws. This holds the parts together more securely but you can still modify it if you wish to. We can build robots with meccano too.  The pain system would have to be modified of course. (Blog of 31 March 2016)

Adafruit microcontroller

Asa H frequently uses multiple microcontrollers in order to control various parts of its robot body.  (See, for example, my blog of 14 December 2015 where Lego NXT brain bricks were used.)  As a possible lower cost substitute I have bought and will evaluate one of the adafruit boards.

The multi-microcontroller architecture makes it easier to add additional functionality over time.  (See, for example, H. W. Lee's MSc thesis from Cornell University, May 2008.)

Finishing up

Again, engineering is a bit more straightforward than science is.  You know you are finished with a project when you have a useful working product that performs the functions you had intended.  (Of course, even in engineering, there is frequently the ongoing maintenance work or the need/desire to incorporate improvements.) But science is less clear cut. Yes, there is the work, finish, publish sequence but even after publication of some work there is usually more that remains to be done.  I tell my students that you declare a project finished and move on to something else when:
1. Funding runs out on that project
2. Time runs out on that work
3. Your employer puts you on another project
4. You are seeing nothing new
5. You find something else that you could better spend your time on.

The concepts of "best" and "better"

I have argued that with vector utility/value there is no such thing as "the best college." (See chapter 2 of my book Twelve Papers, at www.robert-w-jones.com under "book".) Similarly, it may be that there is no such thing as "the best of all possible worlds."
 But world A might be "better than" world B. Suppose the vector value of worlds had only 2 incommensurable components (x,y) and that there were 3 possible worlds with:  W1=(1,2), W2=(2,1), and W3=(3,1).  Then W3 is better than W2.  They are equally good according to component y and W3 is better than W2 according to component x.  But we can not judge which of the 3 worlds is the best of all.  W2 and W3 are better than W1 according to component x but W1 is better than W2 and W3 according to component y. If some one world had the highest value for ALL of the components (x,y,z,....) only then does a "best of all possible worlds" exist.