Wednesday, January 29, 2014

Expanding Asa H's ontology

As a part of Asa H's initial ontology (see blogs of 14 and 16 Feb. 2013 and 12 March 2013) I used  some preprocessor modules to recognize (and define) characters (e.g., letters and numerals). I have begun to develop (sometimes "train") similar modules to recognize/define various objects and features.  These modules can either try to recognize an input (frequently an image) obtained at a single instant in time or a sequence of inputs obtained over a (typically short) time period.  Time varying input is needed where an action is being defined.  A human can also serve as the "preprocessor", perhaps on a temporary basis.  Asa H can also ask for human advice if it is unsure of what it's own preprocessor is seeing. Not all of these preprocessors are being added to the same Asa H agent.  Rather, I am developing a number of individual "specialists."

Monday, January 20, 2014

The poor have too little because the rich take too much

Oxfam has just reported that the richest 85 people have as much wealth as half of the world's population combined! (~3,500,000,000 people!)

Friday, January 17, 2014

Advanced radiation protection?

In order to have radiation-free nuclear reactions (the purported LENRs, "cold fusion") it would be necessary that " could fractionate such large MeV quanta into millions or even billions of smaller quanta." (P. L. Hagelstein, Infinite Energy,  issue 112, pg 12, 2013, see also my sci.physics.fusion post of 1 April 2004 and paper in Kansas Sci. Teacher, vol. 7, pg 12, 1990)  If one had such a mechanism it might be even more important for use as general radiation shielding.

Wednesday, January 15, 2014

Explanatory pluralism (and emergence)

"reductionism that privileges a particular level of explanation over others neglects the fact that mechanisms of different scale are most appropriate for explaining different phenomena."  Paul Thagard in Hot Thought,MIT Press, 2006, page 272

The point is, we find patterns in time and in space at various different scales.  One need not describe the mating habits of butterflies in terms of the dynamics of quarks.

Sunday, January 12, 2014

Vector values again

Paul Thagard has done substantial work on coherence/consistency of thought (see his books Hot Thought, 2008 and Coherence in Thought and Action, 2000).While I do not agree with the exact algorithms he advocates (see Iris van Rooij's review "If Hot Coherence is Rational, then How?" for reasons) I do think it is significant that he employs a vector value/utility (having vector components representing 1. how much you like a given idea and 2. how much you believe this idea ).

Tuesday, January 7, 2014

The problem of contingency

The problem of contingency:  "Why this universe and not some other?"

Tegmark considers that "some subset of all mathematical endowed with...physical existence" (M. Tegmark, Annals of Physics, 270, pp1-51, 1998). In later papers Tegmark suggests that ALL mathematical structures have physical existence and then that all finite computable structures have physical existence (Foundations of Physics, 38, pp101-50, 2008).

In my view:

Observing (interacting with) the physical world we learn/record a collection of patterns and procedures (action patterns/sequences). We learn to count,  to gather objects together (form collections), to add objects to a collection (add), to remove objects from a collection (subtract), to compare collection sizes (equate), to divide collections into a number of equal size smaller sets (divide), etc., etc.  Science studies the patterns we see in the world of our experience, the "physical world."

In mathematics we study patterns, both those we see in the world and any patterns that we choose to make up.  We combine elementary patterns, divide them up, recombine, etc.  Some of what we compose is then found to occur in the world, some is not.  (We see horns in the world.  We see ponies in the world.  We combine these to form unicorns.  We don't happen to find unicorns in the world of our experience.)

My artificial intelligence Asa H thinks in this same way.

Wednesday, January 1, 2014

AI dreams

In Asa H sequences from memory are extrapolated and the resulting synthetic sequence is evaluated for its potential usefulness.  Various AI systems may use (mental) simulations (Artificial General Intelligence, Goertzel and Pennachin, eds., Springer, 2007, pg 353) to judge the usefulness of such extrapolations.  This might be considered "dreaming." 

AI sleep

We usually say that AIs don't sleep and count it as an advantage they have over humans.  But this is not entirely true.  There can be (long) periods of time when no outputs (or output change) is warranted from the AI.  A mobile robot may need to remain static when it recharges its batteries (for example my 3 roombas).  There can be extended periods of time during which inputs don't change much (see my blog of 1 March 2013, item number 1).  This can be related to periodic variation of the environment (like night time if visual senses are involved).  These result in a period of low (or zero) activity for the AI.  Of course this may be avoided if a distributed multiagent system is involved.

Even internal activity ("thinking") may sometimes be reduced.  There may be times when the AI is organizing/sorting its memory (perhaps to permit faster memory search at future times). Time may be spent finding and resolving conflicts/contradictions in memory.  In Asa H time is spent normalizing or renormalizing new or modified case vectors (assuming that a dot product similarity measure is going to be used).  Times may also be spent doing things like defragging and garbage collection.

An AI might sleep.

Conscious machines

If Anderson is correct ACT-R is conscious (How can the human mind occur in the physical universe?, John R. Anderson, Oxford U. Press, 2007, pg 244).  I have ACT-R running in my computer lab.  In my blog of 29 June 2011 I have also argued that Asa H may be conscious.

Mechanical life

If Adami is right AVIDA is alive (Introduction to Artificial Life, Christoph Adami, Springer-Verlag, New York, 1998).  I have AVIDA running in my computer lab. In my blog of 19 Oct. 2010 I have also argued that Asa H may be alive.

Heredity versus environment

During simple/brief experiments Asa H's behavior is dominated by heredity, i.e., its innate algorithms plus any case base loaded as input (see my blog of 26 Aug 2013). During longer and more complicated experiments Asa H learns from the complex patterns it sees in the world and its behavior comes to depend more on environmental influences.  In some experiments the new case memory acquired during Asa's operation can exceed the size and complexity of the original Asa H software package.  As Asa lives longer nurture may come to be more important.  Is the same thing occurring in nature as animals live longer?

G.O.F.C.S., good old-fashioned cognitive science

Asa H. is in the tradition of good old-fashioned cognitive science in its use of processes like memory, classification, feature detection, analogy, etc.  It is original in some of the details, like its use of vector value systems for example.