Friday, April 29, 2016

Attention

Over the several decades that I have been doing AI research the biggest problems have been the related issues of control of complexity and focus of attention.  Can my current AI, Asa H, be taught what it should attend to?  Can the most important cases in each level in the memory hierarchy be taught sufficiently high utilities and, most importantly, will this exhibit the required dependence on context? Does having vector utility help? The utility of a given case (pattern/concept) depends upon the context. The problem of control of attention often times didn't arise in simpler domains but is important for operation in the real world.

Examples of vector utility

If you buy a resistor its usefulness in a given electronic circuit depends upon, at least, its electrical resistance, R, and the power it can withstand, P.  It has a vector utility of at least U = (R, P).  The utility might also depend upon the dollar cost of the component and its physical size as well.

If you buy a capacitor its usefulness depends upon, at least, its capacitance, C, and the maximum voltage it can tolerate, V.  Its vector utility is then, at least, U = (C, V). No single scalar utility can be assigned to the capacitor unless you can specify its application.  If the capacitor is to store charge, say as a memory cell, then perhaps a suitable scalar utility would be U = Q = CV.  On the other hand, if the capacitor is intended to store energy, say in a capacitor bank, then perhaps a suitable scalar utility would be U = E = .5 C VV.  If you wish to store charge while using a minimum energy then perhaps U = Q/E = 2/V.  A suitable scalar utility depends upon the context at the moment. A general utility needs to be a vector. (See chapter 2 of my book, Twelve Papers, www.robert-w-jones.com , book.)

Monday, April 25, 2016

Is the universe a computer?

"What is computation?" was the subject of a 2010 ACM symposium and "what is the nature of reality?", the universe, is an open question in philosophy. In my blog of 28 Aug. 2012 I suggested that a computer might best be described as a reconfigurable causal network. In the classical physics clockwork view of reality the universe certainly is a causal network.  The problem is its not all that reconfigurable.  The big bang did the configuring and that's hard to change. Perhaps equate a multiverse with a computer then. Provided there are a variety of initial conditions.
 If you mean by "the universe" only that portion of reality which is external to yourself then your actions might do a tiny bit of reconfiguring, but not much. You plus the universe would be a coupled pair of computers/Turing machines. I run some Asa H simulations in this way. (See my blog of 10 March 2016.)
One can generalize these notions to a quantum computer and a quantum mechanical reality/universe.

Saturday, April 23, 2016

Reconceptualizing reality

As evolution changes the uses of things, both physical things and mental things, it also necessarily changes their meanings.  So ontologies must change over time.  Usually these are small and gradual changes.  Occasionally they are the more profound changes I have been thinking about like the transition from classical physics to quantum mechanics or relativity theory.

Friday, April 22, 2016

It From Bit?

If I am serious about the possibility of reconceptualizing reality I should be willing to at least consider John Wheeler's It from Bit postulate. To do this I am reading Aguirre and Foster's It From Bit or Bit from It, Springer, 2015.

Actually, the history of a computational reality notion dates back to Konrad Zuse. Zuse called it the computing universe. See, The Computer - My Life, Springer-Verlag, 1993, pg 175.

If all we really experience is Hume's bundle of perceptions or Lewis' observational terms it might make sense to ground our ontology on information. One could stop there and call it idealism?

Thalos has attacked the idea that we should be trying to describe everything on some one single lowest level of reality (See, Without Hierarchy, M. Thalos, Oxford Univ. Press, 2013).  Others suggest there is not one single "correct" or "best" ontology. (See, The Logic of Reliable Inquiry, K. Kelly, Oxford Univ. Press, 1996 and Constructing the World, D. Chalmers, Oxford Univ. Press, 2012) This is in line with scientific pluralism.

Asa H's ontology seems to evolve over time and depend upon the order in which it receives its experiences.

What is the "best" ontology will depend on what I'm using it for.  Quantum fields might be the best description of ultimate reality but they would not be the best vocabulary with which to talk with friends in daily life.  They might not be the best basis for a private language or language of thought either. This was a reason for adopting scientific pluralism. Even in a single branch of science one might find use for several different "languages." The Heisenberg picture of quantum mechanics versus the Schrodinger picture for example. Are wave functions a function of time?  Are operators a function of time? 

It would seem that we need several different (but possibly overlapping) ontologies. And I expect these to change over time.

Thursday, April 21, 2016

Actions

Is all that we can "directly know" just our sense impressions (input signals)? That is, Lewis' "observational terms", O-terms. Hume said "...only the successive perceptions constitute the mind." (A Treatise on Human Nature, 1739) Asa H does learn just such sequences of sensations.  But for Asa H as well as for humans there are also actions (output signals).  And these are important for optimization/intelligence. Simple observation versus full blown experiment.  In Asa H extrapolations, deductions, etc. serve as hypotheses for future testing and correcting.

Wednesday, April 20, 2016

Complexity and diversity

I am reading the book Complexity and the Arrow of Time by Lineweaver, et al. (Cambridge Univ. Press, 2013)  Perhaps the problem is that complexity and diversity are again simply the names of vector quantities, quantities having components like: genome length, the number of cell types, the number of niches, the number of species, the specialization of body parts, the number of component functions, etc. (If these things can be measured.)