My minimum computer lab

A desktop PC running Windows (with printer, scanner, camera, and web access)

A MAC laptop

A netbook running Windows

A netbook running Linux

A tablet running Android (plus an external keyboard)

Pocket computer

(Network at least some of these.)

Programmable pocket calculators

Microcontroller

Digital powered breadboard and chip set

External harddrives, diskdrives, and CD ROM

Software including: Solaris OS, Office Suite, drawing/graphics package, statistics/plotting package, C++ development environment, JAVA development environment, BASIC development environment, PROLOG development environment

Media: CDs, floppies, USB drives, memory sticks, SD cards, etc.

Thorough documentation for all of the above.

Simple circuits versus practical circuits

Students need to be taught the distinction between "simple" circuits and "practical" circuits.  A simple circuit has the minimum number of components necessary to perform its function. It is used to explain how the device (oscillator, amplifier, logic gate, etc.) works.  If you build the simple circuit it may take some adjustment ("playing") in order to get the device to function and its performance may be poor.  A practical circuit will typically have far more component parts but will function reliably.  The practical circuit is the one you will use regularly out in the world.

Milestones

People who have difficulty in maintaining effort and finishing large or difficult projects may find it easier if the project can be devided into many smaller tasks/steps, each to be completed as a "milestone."

Discovering with Asa H 2.0

Asa H 2.0 (see www.robert-w-jones.com, Book, chapter 1) is based on a general theory of thought (see www.robert-w-jones.com, Philosopher, theory of thought and mind).  If this theory is complete Asa H should be creative.
A mobile robot controlled by the Asa H 2.0 algorithms (and fitted with a sensor array which includes external force sensors and internal accelerometers) has been able to discover an approximation to Newton's second law of motion (F=ma).
Asa H concludes that the robot's acceleration is related to the force that acts upon it.  When the robot is carrying a load (added mass) Asa H notes that the robot's acceleration is reduced. (Force sensors in the robot's undercarriage could weigh the robot and it's cargo and make this relationship quantitative.)
When two mobile robots are controlled by the same Asa H brain and one pushes on the other an exact version of Newton's third law of motion is discovered (Fa = -Fr).  The same law can be discovered when  the two arms (or fingers) of a single robot push on one another.

Portability of Asa H

Versions of Asa H 2.0 (see www.robert-w-jones.com, Book, chapter 1) have been run on Windows, MAC OS, and Linux machines.

Evidence for the existence of other spaces

We live in a 4space (length, width, depth, and duration) but there is evidence that other spaces exist too.
1. The success of quantum mechanics is evidence for a Hilbert space in which the wavefunction exists.
2. String (and other) theories suggest the possibility of compactified extra dimensions.
3. The Everett version of quantum theory argues for parallel worlds.
4. General relativity with multiple sheets.

Managing expectations in education

Only small amounts of learning are possible since learning is an NP complete problem.

Mind and brain

If a computer is a reconfigurable causal network then perhaps a mind can be best thought of as a self reconfigurable causal network (or a self reconfigurable influence network).

Quantum computers

If a conventional computer is a (large) reconfigurable causal network (see my blog of  28 August       2012) perhaps a quantum computer should be thought of as a reconfigurable influence network.

Value change

It may be that values should change on multiple time scales.

My Asa H architecture is topped by a value module (see Trans. Kansas Acad. Sci., vol. 109,
no. 3/4, page 159, 2006, figure 1).  This can consist of a value network like that in my 21 Sept. 2010 blog. Slow (long term) value change can be made by turning this Bayesian network into a (time varying) dynamic Bayesian network.

A module for (an additional) more rapid value change might be built from a subroutine that measures recent success (utility and utility change), a subroutine that measures current risk tolerance, a subroutine that measures recent degree of change in the knowledgebase, a subroutine that measures current system damage, a subroutine that measures current needs (like energy, hardware, etc.), etc., and a routine that selects (and resolves conflicts between) these subroutines.

Which devices?

Rather than trying to have one device (a smart phone?) do everything I tend to prefer having many devices, each optimized for doing one or two things.

The miscellaneous category (in a casebase)

If a case is "far enough" away from all existing clusters (categories), and  <N other cases have been found that are "near" to it, then add this case to a "miscellaneous" category.

Search and employ the miscellaneous category as if it was a cluster of its own. (But do not define a mean and standard deviations for it. It is not compressible.)

Remove a case from "miscellaneous" and form a new cluster if and when N is exceeded (i.e., when enough cases like this one are discovered).  (A reasonable value for N might be estimated/arrived at by looking at the number of cases found in all the other categories; the mean and standard deviation of this number. N should be set a few standard deviations below the mean. The size of the "miscellaneous" category should also be kept similar to the size of other categories.)

What is evil?

Is evil simply a result of the imperfect human value system? i.e., a mechanical imperfection.

Mars sample return

There is considerable debate over the costly (perhaps 4 billion dollar) Mars sample return mission.
(A sample collecting rover for the project could, itself, cost 2.5 billion or more.)  In an ideal scenario the Curiosity rover might find something so interesting (potential life?) that we would want to go bring ITS samples back.

AI

Humans are born with a great deal of knowledge built into them by their DNA.(see Chomsky for example)  This was obtained from hundreds of millions of years of learning (by evolution).

AI might be impractical if knowledge learned during an AI's "lifetime" turns out to be small compared to what has to be built in to the AI to begin with. (i.e., to even get it to BE intelligent)

Asa H 2.0 light (see my blogs of 10 Feb. 2011 and 14 May 2012) has a minimum size of 8-9 kB (depending if its coded in BASIC or C++).  A casebase (knowledgebase) of about 50 simple cases has been learned by Asa H 2.0 light and has a size of about 10 kB.

UBL

Ideally, Bin Laden would have been arrested, tried, and convicted by a neutral/impartial jury in the Hague and sentenced to life in prison.  This may have been impossible but perhaps we should have tried.

Tax only the rich

I just got an email from newsmax.com which states "According to Federal Reserve data, the wealthiest 1% of Americans now have a greater net worth than the bottom 90% combined."  Assuming that this is accurate the federal government should only tax the top 1%.  The rest of us have nothing to give.

More on interstellar travel

Our DNA represents the end product of hundreds of millions of years of learning. Any intelligent recipient would want to preserve and make use of it.  For that reason I would expect them to recreate us. (see my blog of  11 May 2012)
Note: With generational starships the original astronauts don't get to their destination either.

laboratory experiments

Ideally, everything we teach, everything we believe, we would test/demonstrate in one or more laboratory experiments.  But this is impractical.  Learning from experience is slow and costly. It would take too long to "PROVE" everything, and we don't have the equipment to do it.  It would cost a great deal to obtain all the required hardware.

If standardized student test scores were the proper measure of performance we might do no experiments, no hands-on work at all. 

But experiments are where new knowledge comes from.  As profession scientists we must do experiments.  (Or at least some of us must.)  Even when we are "just teaching" students need to see some experiments even if this learning method is "less efficient."  Students need to see examples of how new knowledge is obtained.  Students need to see some subset of our beliefs "PROVEN."  We can all argue over how much time and money to spend on this. (Neither can these experiments all be computer simulations.  I've argued previously why computer simulations are not as good as real experiments. see my blog of 17 Sept. 2010)

Being a scientist is being human

The figure below is roughly that from page 1045 of Russell and Norvig's Artificial Intelligence: A Modern Approach, 3rd edition.  It is a simple description of what it is to be human. (Of course it's oversimplified, it takes up less than a page!)  We look at the world with our senses and observe what it is like.  We have some idea of how the world evolves, what actions we can perform, and what our actions do.  We use a value system to decide what is best to do at any given moment.

A scientist does the same things.  S/he may simply put more effort into it, work harder and more carefully at it.  Scientists sense the world, perhaps with refined instruments.  We want to know what the world is like, perhaps in more detail than the man-on-the-street.  We want to know how the world  evolves, again, perhaps in more detail and on various scales.  As scientists we act, perhaps augmented by machinery.  Hopefully we use a more refined value system (see my blog of  21 Sept.  2010) whereas unaided humans have a simple network of drives and aversions.

We are all scientists.  To be an intelligent creature is to be a scientist.  As professional scientists we just work harder at it.  Scientism is in our inherent nature.

Scientism

I advocate scientism, the "belief in the universal applicability of the scientific method and approach, and the view that empirical science constitutes the most authoritative worldview or most valuable part of human learning" (Wikipedia, scientism).
There are, of course, various versions of scientism, some stronger than others.  I believe that all knowledge is of an approximate character and human capabilities are limited and limiting. Human science has boundaries/limits/limitations.
E. F. Schumacher (in A Guide for the Perplexed) claims science (and scientism) is confined solely to what can be "counted, measured, and weighed."  Clearly he is wrong.  The wavefunction can not be so measured but is an important part of science.
I don't believe science is (or can be made) value-free (or value-neutral).  Values are needed and used whenever we make decisions/judgements of any kind. I advocate some sort of value system like that in my 21 Sept. 2010 blog.
I do not advocate any single perspective, rather I advocate a "scientific pluralism" (see my 26 Sept. 2010 and 17 Aug. 2012 blogs).

The X Files

One can assemble huge "databases" of faulty results (see my 2 April 2012 blog).  I have about 1 file drawer which contains my more controversial collection of articles. 
On the higher quality end are the space drive articles like Jack Wisdom's Swimming in Spacetime, Science, Vol. 299, 21 March 2003, pg 1865 and Campanelli, et al's, Maximum Gravitational Recoil, Phys. Rev. Letters, Vol. 98, 231102, 8 June 2007.
Other papers in this file include, for example, work on time travel (like F. Tipler, Phys. Rev. D, vol. 9, num. 8, pg 2203, 1974) and solid state ("cold") fusion (like Fleischmann and Pons, J. of Electroanalytical Chem., vol. 261, num. 2A, pg 301, 1989).
Besides journal articles there are also books in the "X Files," like Tipler's The Physics of Immortality, Doubleday, 1994 and Mallett's Time Traveler, Thunder's Mouth, 2006.

Is a computer a reconfigurable causal network?

I've just read the published proceedings of the 2010-2011 ACM Ubiquity symposium on the Turing question "What is computation?"  (The Computer Journal, Vol. 55, num. 7, pg 799, 2012)  Is a computer simply a reconfigurable causal network (including possible feedback)?  I think of "information" as "knowledge", see my blog of 25 Feb. 2012.

my library needs some work

It took me some time to find my copy of the book Hypercomputation.  I was not even sure if it was at home or at work (ESU).  I need to do some further organization.  At the moment perhaps half of my books are organized into catagories like:
computer science
artificial intelligence
machine learning
neural networks
AI textbooks
robotics
weak methods
creativity
case-based reasoning
programming languages
logics
statistics
electronics
physics
fusion and plasma physics
natural language
cognitive science
mathematics
philosophy
spaceflight
socialism
fiction
(each of these can be subdevided in turn)
I need to organize as much of the rest as I can.
My file cabinets full of journal articles and lab reports are in better shape (perhaps 95% organized) but also need work.

Changing what science is and how it's done

Having multiple overlapping theories of a knowledge domain is better than having just one.  For more than 50 years I have been following this scientific pluralism (see my Sept. 26, 2010 blog for examples).  What follows is a Bayesian argument for scientific pluralism following Cheeseman (in The Mathematics of Generalization, D. H. Wolpert, ed., 1995 and references therein).  Conventional science can be seen to be an approximation to scientific pluralism.

american exceptionalism

American exceptionalism is a bad idea.  It gets in the way of americans learning from other people.  It gets in the way of  learning from countries with higher standards of living than us and countries with better health care systems than us, etc.  Starting a war is murder.  A goal of spreading democracy doesn't change that.

forgetting, death, and extinction

Forgetting is part of learning on each level of  (some versions of) the Asa H hierarchy. (And similarly for other examples of machine learning.)  Death is forgetting at the level of the whole individual. (Further up the hierarchy if you will.)  Extinction is forgetting at the level of the whole species. So death and extinction are not bad.  (Though they may come too soon in some cases.)  How quickly forgetting should occur depends in part upon the size of the memory that is available and speed of memory access.

Software maintenance issues

Operating system changes that affect language functionality.
     example:  changes to Windows affecting qBasic functionality,
                     switch from qBasic to QB64
                     changes to MAC OS X affecting chipmunk Basic functioning
Language changes that affect program functioning.
     example: C++ library changes affecting Asa H functioning
                    C++ on Linux versus MSWindows
Functionality affected by program growth.
     example: Prolog crashing sooner as knowledge base is grown
Adding external disk and/or CD drives to enable continued use of old media.
Backups guarding against media failures.
Porting AsaH to the new tablet computers (and their operating systems).

Multiple proofs are better than one

Having two or more proofs (arguments/derivations) is better than having just one.  All real logic is fuzzy (approximate) in the sense that each logical step may be wrong (at least some of the time) and each quantity being manipulated is only a rough (approximate) description of something observed in the real world.  In some idealized logics 2 proofs may be no better than 1 proof.  In some more realistic logics 2 proofs are better than just 1.

"Waldos" as natural language input and output devices

Telemetric input and servo-powered animatronic output "Waldos" (see wikipedia, "remote manipulator") can be used to input and output sign language.  200-300 signs (American Sign Language, Spark Charts, 2004) would cover about 2/3 of conversations while 2000-3000 signs (American Sign Language Concise Dictionary, M. L. Sternberg, Collins, 1994) would cover about 95 % .  Each sign would be stored as a brief script.  Input to a telemetric input Waldo would be recognized by matching against the recorded script (case vector).  Output would be accomplished by sending the recorded script to a servo-powered animatronic output Waldo.

I see this as an extension to the way in which protolanguage was used by Asa H.  See chapter 1 of my book "Twelve Papers" (www.robert-w-jones.com, Book).  Each of the 3000 or so signs can be recorded in a single pass from an input Waldo.  Association of these signs with events that occur in the world (and "meaning") is then learned by associative learning in the usual way by Asa H.

crime and insanity

Some crimes themselves constitute sufficient proof of insanity.

aurora colorado

I don't know how you get into a movie theater with a rifle and shot gun.  We need better gun control laws in this country.

NOAA climate change report

A report from the National Oceanic and Atmospheric Administration concludes that human carbon dioxide emissions (man-made climate change) contributed to last year's drought in Texas and Oklahoma.  That's kind of fitting since these states are the home of so many right wing nutcases who are antiscience.

Alternate realities again

I just had cataract surgery and received an intraocular lens implant.  I must have slowly come to see white as offwhite.  My new lens now allows me to see white while my remaining old eye sees white as a bit yellow or brownish, like aged, yellowed paper. We don't all see the world the same.  The way the world looks depends upon OUR senses.  The sky is blue (in part) because of our senses.  Birds, for example, see it differently.

Ways of knowing (again)

Along the lines of  my blog of 14 Feb. 2012 Johan van Benthem says there are 3 main ways of knowing: 1. Deduction from valid premises. 2. Observation. 3. Asking an authority. (from Where is logic going and should it? to appear in What is to be done in philosophy, E. Bencivenga, ed.)

Blogger oddities

I enter an upper case I in my draft.  When published it appears lower case.  I go back to the draft and it's upper case there.
Spacing in the draft differs from spacing when the draft is published.  Two lines are left blank in one, one line in the other.
Items that are lined up in columns in the draft are not in columns when published.  But if you go back to the draft they are lined up. (Example, LISP and PROLOG in my 5 June 2012 blog.) When I go to "edit" versus "view" they are also different.

Ava, a virus AI

Asa H 2.0 (see my blogs of   10 Feb. 2011 and 14 May 2012) can be made the payload of a computer virus (The Little Black Book of  Email Viruses, Mark Ludwig, Createspace, 2009 and Hacking, Jon Erickson, No Starch Press, 2008 ).  When released onto a computer network the infected machines will communicate with one another by email, turning the network into a large parallel AI computer.  I have written the code for such an Ava 1.0 but do not currently own a computer network on which I could deploy, debug, and test Ava so I have only been able to perform small scale debugging and testing. (I bought a router and have networked a couple of my computers.)

Renovation

They're tearing out the windows and part of the outer walls of our building (Science Hall).  When we were first told about this we were told that all the work could and would be done from the outside.  I am now hearing that they must get into and move tables and shelves and file cabinets in my office.  The restrooms have been closed for a week and I've seen very little done to them.  We'll see how much this interferes with research.  My summer class will end this week so I hope it will not feel an impact.

Experimental programming

A major portion of AI (and computer science in general) is experimental programming.  It's surprising then that there is no good monograph on the subject. (There is chapter 6, Towards a Discipline of Exploratory Programming, in Partridge's book Engineering Artificial Intelligence Software, Intellect, 1992.)  One could at least write a history of what's been done in the past.  This might suggest some paths forward.  Such a history might include:

experiments with various algorithms
specialized languages like:  LISP
                                             PROLOG    ---    and logics
                                            OPS 5/CLIPS   ---   rule based systems
                                            NIAL   ---   diagrammatic and spatial reasoning
IDEs
parallel computing efforts
networks
flowcharts  ---   UML
various architectures
search of various sorts
incremental software development

One can obviously experiment by:

changing architecture
changing algorithms
changing language used  (which language is best for which task? what features of each
language are important for what?)
adding pieces, functionality (incremental development)

The KADS methodology is one source of information about what architecture or algorithm to use for what task.

Just how portable is C++?

C++ is perhaps the most popular language for AI programming.  I find, however, that my Asa programs in C++ will compile and run with some C++ compilers but not with others. (At least not without some workarounds.) I understand that some of the libraries have been changed in the last couple years. Just how portable is C++?  (The code in my 14 May 2012 blog will run with the Dev-C++ compiler but not MS C++.)

Flood?

I got a phone call from the ESU campus police at 1:00 AM last night.  They said "science hall had 2 inches of water in it."  If so I figured that the planetarium was completely under water again!  I've also had small "floods" (more like leaks) in the past when some cooling line or other broke on one of my plasma experiments.  Usually I'm on site when such an event occurs. This morning I went in early with a pair of old shoes and extra socks.  Turns out that someone was doing plumbing in several of our students labs late yesterday.  Somehow they caused a sink in my plasma lab to overflow sending some water into my office as well.  Fans have dried up a lot of the water but I will have to throw out more than a dozen books that were on the floor.  I'll replace some of those.  I also had 3 old conference posters that are wet and will be discarded. I am not sure about the condition of the older "tower" computer under my desk.  It was old but still in service. (I tend to do different things on different machines.)  The surge protectors and computer cords under my desk seem to be OK.  I'm writing this on my desktop. A couple of piles of books had been knocked over, perhaps in the cleanup work.  This caused a few more books to be wet.  Time will be the biggest loss.

More Asa H. 2.0

There are many versions (>100) of Asa H .  The following is a "light" version in C++ that was developed with the help of Patrick Devlin at Rutgers University.

A more practical sort of interstellar travel?

Various radio messages have been beamed toward nearby stellar systems.  I contributed to one a couple years ago.  (My contribution was a warning to anyone who got the message.  I warned of humankind's rather imperfect value system.)  But perhaps we should send the complete digital description of the human genome.  Or perhaps those of various humans.  Along with this would be an attempt to explain what the message is.  One might hope the recipients could then construct human beings at their end from atoms available there.  Perhaps spaceships aren't needed. And perhaps a larger fraction of the space budget should be spent on seti. As a hedge against global catastrophe we should begin to send such signals now.

Roomba again

My roombas like to go under my bed and try to eat the electric blanket and lamp cords.  This sometimes traps the roomba.  It would be quite hard to make a cord detector and avoidance system. Asa H wouldn't help here. Once again, roomba works well but only in a clean, simple environment. This is a common and fundamental issue with current AI.

Asa H 2.0's ancestral descent

Asa (autonomous software agent) is my AI project which began in about 1994-95. Asa F 1.0 was built from artificial neural networks (in an architecture like that of Richard Sutton's thesis, 1984) and early results were published in Trans. Kansas Acad. of Sci., vol. 100, num. 3-4, pg 85, 1997.  Results from a version built from case-based reasoners, Asa F 2.0, were presented in Trans. Kansas Acad. of Sci., vol. 102, num. 3-4, pg 117, 1999 and Trans. Kansas Acad. of Sci., vol. 107, num. 1-2, pg. 32, 2004.  A hierarchical version, Asa H 1.0, was described in Trans. Kansas Acad. of Sci., vol. 109, num. 3-4, pg. 159, 2006.  The current Asa H 2.0 versions (see my 2011 book "Twelve Papers") employ revised representations (see my 22 Nov. 2010 blog) and have made use of parallel compution. An open source  "lite" version of Asa H 2.0, with a fair amount of documentation, is presented in my 10 Feb. 2011 blog. Many experiments with these Asa packages have been reported in my various publications since 1995.

Plasma/fusion energy research

A colleague asked me why I was no longer doing plasma/fusion research.  I could have answered that there was some original plasma/fusion work published in my book "Twelve Papers" just last year, in October 2011.  But the plasma/fusion work presented in that book was some of the oldest work in a volume that took many years to write. So my answer instead was that in the united states support for plasma physics and magnetic fusion energy has declined substantially since the early 1980s.  (It's true inertial confinement spending went up but some of that must be considered military research, not plasma/fusion energy.)

Complaint about laptop keyboards

I don't like how laptops leave open, unused space below the keyboards.  I prefer my old TRS-80 Model 100 in that regard. (Model 100 also had good battery life.) I've been told people like the empty space to rest their hands on.  But typewriters didn't have any such space.  I will admit that as someone who "hunts and pecks" I don't hold my hands the same way a touch typist does. (Like a numeric keypad a touch pad/trackpad would best be placed to the right of the keyboard.)

Hello World

I never write "hello world" programs.  I just installed Python (and Prolog) on my Linux based netbook.  Since any program can be built from sequences, loops, and decisions I tried Python out on:
a sequence of commands
a=2
b=3
c=a*b
print c

a simple loop
for x in range (0,4):
     print x

and a simple decision structure
a=5
b=3
if  a==5:
     print b
else:
     print a

With AI software I frequently try something like:
human(bob).
mortal(X):-human(X).
?-mortal(bob).

Linear utility functions and assessment

When we assess job applicants, or employees, or rank grant applications we typically use a linear utility function.  We take things like the number of years in teaching, the number of papers published, the number of talks given, etc., multiply by some weighting number, and sum up to a single numeric score.  It is easy to show how poor an approximation such a linear model is likely to be.  For a scientist or academic an IQ of 120 would be quite reasonable but an IQ of 60 would surely be hopelessly low.  A linear model involving IQ is surely a poor model.  A nonlinear model, with IQ raised to some power, would certainly be needed.  When we use a linear model we are simply hoping the approximation is good enough.

An advantage to being an engineer II

I have previously described some advantages to doing engineering work rather than science (21 Jan. 2011).  Another advantage to engineering is that the prior probability of succeeding in an engineering project can be higher than the prior probability of succeeding in a scientific investigation.  This is because engineering projects are usually based upon more well established knowledge.  Hence the higher prior probability.

Education reform

Programs like "no child left behind" expect too much.  Learning is, in general, an NP complete problem. Learning will never be easy.  Neither will it be cheap and all too often the reformers want it to be cheap.

The achilles heel of scientific pluralism

I advocate scientific pluralism (Scientific Pluralism, S. H. Kellert, et al, U. of Minn. Press, 2006)  in both science and engineering (and in pretty much everything else I do, see my 26 Sept. 2010 blog post).
But one must maintain a strong skepticism.  Most published research is erroneous (Why most published research findings are false, J. P. A. Ioannidis, PLoS Medicine, August 2005) and one can assemble huge "databases" of faulty results (see, for example, www.rexresearch.com).  Just because we accept two or more different theories/models does not mean we can be any less skeptical in our work.

Science on twitter?

Some colleagues attempt to discuss their scientific work on twitter.  While my publications are quite succinct, of my more than 150 blog posts only a very few are brief enough to be tweets.  140 characters is just too few.  280 is only a bit better. A link that would send you to a real blog would just be advertising.  Just start at the blog in the first place.

Capitalism

The capitalists want us  to model every social activity as a market.  I think they would even turn our families into markets if we'd let them.  But science has many models, not just one.  I think that a family is  a good model.  Some of what the capitalists would call markets would better be treated like (modeled as) families.  Two theories are better than one. (Scientific pluralism)  Two models are better than one.

Increasing complexity

Looking across the biosphere one finds a distribution of lifeform complexities.  (In the absence of things like mass extinctions) this distribution TENDS to broaden with time.  The extreme tail of such a distribution then also increases with history, i.e., the maximum complexity of organisms TENDS to increase (but DIFFERENT organisms will be at this extreme peak at different moments.) (AGAIN, the biosphere is an open system, we are neglecting such things as mass extinctions here.)  Today humans are up in the tail of this distribution of complexities.  Perhaps when humans become extinct our machines may survive us and occupy such a position.

Complexity will likely not be maximized by the same lifeform that maximizes longevity. Again, "progress" is likely to be measured by vector quantities.

Progress

For life taken as a whole it is not the lifespan of a single species that matters. (Even if an artificial life  form controlled by Asa H software would have to use that as a measure of utility. see my 19 Feb. 2011 blog) All species go extinct.  Rather, there is a distribution of lifespans (for all the various lifeforms) which grows increasingly more skewed with time.  That change in the distribution is what constitutes progress for life as a whole.  Indirectly (as the tail of the distribution becomes populated) this leads, in turn, to new genera with enhanced longevity. (Contrast this with what might constitute progress for human society.  see my 18 May 2011 blog)

Idiosyncrasies

I use ebooks when I need to reduce volume but I really like the use of marginalia in print books.  Things that don't get into my lab notes do get into my original sources in the form of marginalia. I mark up my books a lot.

I also like numbering every line of BASIC code.  I find it easier to locate bugs and make changes when the lines of code are all numbered.

I can spread out more material on my desk (or lab table or floor) than I can work with on a computer screen.  I really feel the difference between the 3-D and 2-D spaces involved.  2-D feels very constricting.  (With a computer or two running around the room I suppose I'm occasionally using both spaces.)

Signing with a stylus on touch screen devices is really difficult.  The screens are too slippery and held at bad heights and angles.  With age my handwriting has gotten shakey.  I'm fine when I write large, on a blackboard for example.  When I try to write small I am shakey.  On a slippery surface it gets worse.  I don't mind tapping on tablet PC screens but I don't want to draw or write on them.  Could the surface be kept clear but roughened or otherwise made less slick?  Would that help?  Alternatively one could change the stylus.  Writing with something like a sharpened eraser does help some but leaves a residue.

(My) uses for mobile computing

30 years ago I bought a Sharp pocket computer so I could try out programming ideas away from the office or computer lab. (I still do this today.) 20 years ago I still did a lot of library research on site.  I bought several small machines and wrote some software so that I could input/log information in the library stacks as I found it. (I do not do this today. I do not visit libraries or roam the stacks like I used to.) In the last few years I have made more use of electronic documents.  I have several ereaders but prefer larger screens and so also use tablet computers, netbooks, and laptops to read ebooks and pdf documents (publications, theses, etc.). I have occasionally used wireless connections to search the web, access email, and buy books online when away from my desk.

Which operating system to use?

Over the last 20 or so years I have used: several Android distributions (1.6 and 2.2), MAC OS 7, MAC OS X Tiger, Fedora, Ubuntu, OpenWrt, and Xandros Linux, Windows 3.x, 95, NT, XP, and 7,  IBM unix, and openSolaris.  Each has its good and bad points:

Android         pro: optimized for mobile devices
                      con: lacks some applications you would want (for example, a good office suite)

Windows       pro: has many apps available and they run "right out of the box"
                      con: there are some quality/stability issues (solved with Windows 7?)

MAC OS X   pro: quality and stability
                      con: hardware is higher priced

Linux             pro: free and stable
                       con: fragmented, many distributions, each a little different

unix/Solaris   pro: reliable/stable
                      con: hardware specific, lacks some applications


Asa H was built to run on both MACs and PCs.
         

Science and philosophy

When I was an undergraduate the physicist Gerald Feinberg argued that physics had solved philosophy's "Thales problem." (The Journal of Philosophy, Jan 6, 1966) It is well known that other philosophical questions have been resolved by science. My own philosophical work has been mostly in this tradition, trying to make use of progress in the various fields of science in order to settle (or at least clarify) issues in philosophy (see my 1 January 2012 blog for example, "The big questions"). Conversely, philosophy may suggest areas that science should investigate.

Limits of (human) thought?

In his paper "The Problem of Philosophy" and his book "Problems in Philosophy", Wiley, 1993 Colin McGinn argues that "The human mind conforms to certain principles in forming concepts and beliefs and theories...and these constrain the range of knowledge to which we have access." In some areas of inquiry "the correct theory is inaccessible to the human intellect."
But the whole idea of "learning" is to have access to patterns you have never seen before.  The mind is an open system. Things get added to it from without.  It can also employ external memory storage (notes, books, libraries, etc.) to augment its capability.

Science versus mathematics

Is mathematics one of the sciences?  If not, how do we distinguish one from the other?  I must admit that I usually think of mathematics as a science.  As a trained physicist I find mathematics to be as much like physics as, say, biology is.

But if I were to look for a distinction between science and math then it might be that scientists (or should I say physicists) look for patterns that are present in the world whereas mathematicians look at patterns that may (or may not) occur in the physical world.

Social Intelligence?

H. M. Collins has argued the "social nature of human beings and their knowledge." ( Artificial Experts, MIT Press, 1990, page 224) He further claims that "there are no stand alone human beings." (page 221) and "socialization is necessary for learning" (page 12).  At one point he claims that a man working alone in a room does little that counts as intelligent! ("If I lock myself up in a room for a day, so that I have no contact with anyone else, when I come out in the evening my knowledge is not much changed." page 12) I guess he believes that all intelligence is collective intelligence.

If I was alone in that room with a physics experiment I believe my knowledge may have increased a great deal!

Also, it occurs to me that the explosion of everything related to "social media" is a  contribution that computers make to society, a contribution from their "social intelligence."

Collins also states that "it is induction that we can do and that machines cannot." (page 132)  I would think that the various "invention machine" experiments show that this is false. (Including my own published work.)

Battery issues with mobile devices

Years ago when I got my first mobile phone I had battery issues.  As soon as I got home or to a destination I had to charge the phone.  Today that's all behind us.  My phone can last several days between  charges.

I have had less luck with mobile computing devices.  I have a small (7 inch screen) tablet computer running Android that I can run off batteries for a prolonged period (likewise with TI-83 and TI-86 calculators running TI-BASIC) but I've had issues with all larger devices.  I have a large (10 inch screen) tablet computer running Windows 7, a netbook running Linux, a netbook running Windows XP, and an ibook running MAC OS X Tiger/unix none of which have adequate battery life.  As a result I typically run all of these plugged into the mains/wall outlet (and this lets me turn up the screen brightness to something closer to what I get from my desktop computers). Fortunately, I seldom go somewhere where I don't have access to a mains electrical supply.  (An inverter works in the car.) It's my impression that the majority of the time people run their laptops off the mains.

The smaller mobile computers have inadequate computing power.  The larger mobile computers have inadequate electrical power.  As a result I currently tend to favor a netbook or small laptop for mobile use. (They also have a reasonable screen size and a real keyboard. see my 8 Feb. 2012 post. They are  lighter to lug around than my physics books.) Perhaps I should/could attach 2 or 3 more batteries in parallel to my Acer Windows XP based netbook.  That might be just about what I'd really want. Perhaps laptops should come with a larger battery option. (Just like they may now come with different storage options.) I know of at least one laptop that offers this but it was only a choice of a 9 cell battery pack versus a 6 cell battery pack.

What is meaning ?

Understanding meaning is sometimes termed "the really hard problem."  Kintsch (in Attention and Performance, R. S. Nickerson, ed., Lawrence Erlbaum, 1980) attributes to Aristotle a feature model of meaning.  The meaning of  "man" is the set of features that a man possesses: "two legs", "two arms", "a mind", etc.  A concept stored in Asa H has such features associated with it (on the next lower level of the memory hierarchy).

Quillian's "semantic networks" were conceived as a representational format that would permit the meanings of words to be stored. Each concept is defined in terms of its associations (links and uses) with other concepts in the network. Again, a network like the one learned and used by Asa H.

What is real?

The best current answer is the ontology created by the sciences:
i.e., particles, fields, space-time, wave functions, atoms, molecules,amino acids, cells, tissues, organs, organisms, etc., etc.
These categories are, of course, tentative, subject to almost certain change. (For example, are there strings?)

What is knowledge?

An "intelligence" is " a system to handle all of the calculations from crude inputs through to overt actions in an adaptive way so as to maximize some measure of performance over time" (P. J. Werbos, IEEE Trans. Systems, Man, and Cybernetics, 1987, pg 7) This intelligence might be the brain of a robot which operates in the real world. An example of such a system would be my Asa H (see, for example, my 10 Feb. 2011 blog).

"Knowledge" is then the set of patterns learned by such a system and used by it to "live." (see, for a simple example, my 22 Nov. 2010 blog or the examples in chapter 1 of my book TWELVE PAPERS, amazon ASIN: B005SVVEYC) In general this knowledge is approximate and fallible.

Print versus ebooks

I have previously commented on ebooks and ereaders.  I use both these and print books.  But one thing has changed for sure; I don't roam the stacks much any more, rather I now do mostly online searching.

Ways of knowing

Is there just a single "way of knowing?" Call it "the scientific method." Or are there various ways of coming to reliable knowledge of the world?  Certainly each scientist works a bit differently.  No two work in exactly the same way.  Methods and standards also vary from one field to the next. Theoreticians may work differently from experimentalists. Deduction and induction.
The extent of human knowledge far surpasses what can be mastered by a single individual.  It would take more than a dozen good scientists to master physics alone.  So one has to trust in "authorities."  You can't possibly do all the experimental tests yourself.  You can't possibly check all of the math proofs.

The right computers

Most of the coding that I do is done at a desktop but I used to have (in the 1980s and  1990s) a Sharp pocket computer (PC-1251) that I could use away from the office to try out algorithms and other ideas. (Its display died after about 20 years. Currently my Texas Instruments TI-86 can do about what I used to do with the PC-1251, but in "TI-BASIC" language.) Today I use a laptop (or netbook) for such purposes.  I own a Dell Axim pocket PC and also a tablet PC but they lack real keyboards.  Just like you need a keyboard if you do a lot of texting I find I also want a keyboard if  I'm programming.  When I'm coding or when I'm reading electronic documents I also want a larger screen than what is available with typical current tablets. (I find the screens on typical ereaders to be too small as well.  They are smaller than the pages of most print books.) I also find Android inadequate as an operating system. (But it is being improved, I've not used Android 4.0.)

Credit for publication

During consideration for retention, tenure, promotion, and raises administrators in academia tend to count 1 physics publication = 1 chemistry publication = 1 earth science publication = 1 biology publication = .....  This is unjust.  Publication rates (and the difficulty of generating original publishable research) are different in different fields (and different in different subfields). (Demographic and economic determinates of scientific productivity, Stephen and Levin, Policy Research Program,  Georgia State Univ., Nov. 1987)

"The Singularity"

My view is different from those who believe in "the singularity."  For me the question is more: "can mankind survive long enough to create independent mechanical life?" This should be one of our goals as a civilization. By "independent mechanical life" I mean mechanical life (see my 19 Oct. 2010 and 30 July 2011 blog posts) that can continue on after we humans have gone extinct.

Why BASIC?

Why so much BASIC language?

The biggest program I've ever written was actually in PROLOG but I HAVE written a lot of BASIC language code.

BASIC is one of the most popular languages for RAD (rapid application development)/ rapid (software) prototyping.  Artificial intelligence research involves lots of exploratory programming. Experimental programming is an ideal place to make use of RAD.

BASIC, being simple, is also good for students (see my Jan. 1, 2012 post on physics without calculus for  example).

Predictive analogy, proportional analogy, and Asa H

There are different sorts of analogy.  Predictive analogy "is the process of inferring further similarities between two given situations based on some existing similarities," Bipin Indurkhya , Predictive Analogy and Cognition in Analogical and Inductive Inference, K. P. Jantke, Ed., Springer-Verlag, 1992. In Asa H predictive analogy is performed by dot product similarity measure between cases. Input vector components are compared between cases and output vector components are inferred.

Proportional analogies are "of the form: A is to B as C is to D" Scott O'Hara, A Model of the 'Redescription' Process in the Context of Geometric Proportional Analogy Problems, also in Analogical and Inductive Inference. In Asa H proportional analogy is performed by vector case extrapolation like: vector V4 = vector V3 - C*(vector V1 - vector V2).

Command hierarchy

I am opposed to command hierarchies (a pyramid of bosses with employees below) wherever they may be found. It's been known for a hundred years that groups can make better decisions than individuals can.  A better system (than command hierarchy) would be something like that described in Maverick by Ricardo Semler, Warner books, 1993. Democracy is both more ethical and more efficient than dictatorship. The workplace needs to be democratic. A country is not free if the workplace is not free. It's sad what we have to pass on to our children.
I suspect that even wars and armies would be better run by a general staff rather than a single field marshal.
Or, perhaps, a group might do better at avoiding war.

ebooks

I have several dozen "ebooks" (about half nook books and about half kindle) and a much larger number of dissertations, lab reports, journal articles, "white papers", etc. (as pdfs)  I have only read three ebooks from "cover to cover" and I did that on large screen devices.  On large screens reading of ebooks is comparable to reading conventional printed books.  I use ereaders when their small size is a virtue.  A family friend who is an avid reader recently traveled to europe with her daughter for a few weeks.  She bought a kindle so she wouldn't have to carry a large number of paper books with her.  ereaders are getting better all the time. (The local Radioshack salesgirl acted like I should buy a new one even though my kindle was less than a year old.)  With my bad vision, however, I still need a large screen in order to make the experience pleasant. Screen size might be less of an issue for people with normal vision. I also have the problem that (as of a couple of months ago) Emporia State's WiFi would not work with kindles at all and only worked with the newer color nooks. (Or so the IT people told me.  I don't have a nook ereader though I have downloaded the Barnes and Noble software and can read nook books on several of my computers.)

The COTS experiment

Since in the US rockets and spacecraft have all typically been built by industry anyway what NASA's COTS program really is is an experiment to see how small an organization can perform spaceflight and how cheaply, reliably/safely. (Clearly there are tradeoffs.  A cheap rocket may be possible but too unreliable/unsafe.)  Since most companies fail (go bankrupt and close) in 3 to 5 years and 90% of companies fail in 10 years this is a very real question and the answer is uncertain.  The two companies that are trying with Antares/Cygnus and Falcon 9/Dragon are currently well behind schedule. It will take some time and some number of flights to determine the reliabilty that results.  COTS is an engineering experiment.

My first computers

In the 1960s I bought 2 Geniacs(which used switches only) and a Minivac 601 (which used relays!), all SMALL logic circuit machines.  I then learned a little FORTRAN (from a book) and bought a Heathkit EC-1 ANALOG computer like the one shown below (it used tubes!). (I still have it today!)  Low cost digital machines didn't exist at that time and we were still using slide rules. (I'm told that Korolyov stood in the russian mission control using his slide rule to calculate orbital parameters.)

My library

Some of my (~2500) books:

Children and roomba

Only 2 small children have seen my roomba in operation; a 2 year old boy and a 3 year old girl.  Both were afraid of the roomba.  I wonder if by making the device in the shape of a dog, let's say, and covering it with fur, one could make it more child friendly.

Some history

Me, 25 years ago, computer interfacing our plasma experiment. The code produced at that time is in my 2 Nov. 2011 post. (and Imad El-Jead's thesis of 1988 from Emporia State University)

Working with my AI, Asa F 2.0, about 10 years ago. Some results were published as Trans. Kan. Acad. Sci., vol. 107, # 1/2, pg 32, 2004.                                   

Today.  Downloading a dissertation to one of my ereaders.

                                                                            

Project-based learning

Project-based courses are popular with students.  I have used projects as 1/3 or more of my digital electronics lab for 25 years.  But projects have their limitations.  I can think of no (small number of) projects that would cover ALL of the topics and details I need to cover in first year physics, for instance.

My book "Twelve Papers"

My book "Twelve Papers" was published last October.  You can download a copy free from my website http://www.robert-w-jones.com/ , Book, or you can buy a copy for the kindle reader from amazon for $1.99 (ASIN: B005SVVEYC) . (I would have made it free if they had let me.) The book covers more than 5 years of work and contains:

1. Experiments with Asa H  (The latest work on my artificial intelligence "Asa H" including initial efforts toward machine consciousness and natural language processing.)

2. Capitalism is wrong ("Wrong" both morally and in the technical sense of being incorrect.)

3. Chaining case-based reasoners

4. Objective analysis of student data  (A paper I have used for a number of years in the student laboratory.)

5. Experiments with machine creativity  (A paper I wrote for, and used as a part of, an honors course in creativity run a few years ago at Emporia State University.)

6. Experiments with a hierarchical ensemble classifier

7. Neural network categorization of experimental data  (A more advanced software analysis of Langmuir probe data.  See my Nov. 2, 2011 blog for much simpler software assuming a Maxwell-Boltzmann distribution.)

8. Quiet plasma in gas mixtures

9. Plasma optimization using data mining

10. The origin of large scale fluctuations in a Roth (bumpy) torus

11. Plasma diagnostics (A handout used in some of my plasma physics courses.)

12. Turbulent thermal insulation with clump regeneration and wall confinement  (Dated, but part of an argument that more effort/resources should be spent on wall confinement of very high beta plasmas.)

The Big Questions

I am interested in trying to answer the big questions.  Here are some of my current attempts:

Q 1. Why are we here?  A. Evolution acting on the animal kingdom.

Q2. What is our purpose?  A. The purpose of all life, to survive (reproduce and spread).

Q3. Why does anything exist?  A. An empty universe may exist but the question then won't arise.

Q4. Did the universe have a beginning?  A. Yes, at the "big bang."

Q5. What is thought?  A. See my blog of 29 Sept. 2010 and papers on my website http://www.robert-w-jones.com/ Asa H reduces MENTAL processes to a series of standard PHYSICAL processes.

Q6. What should humans value?  A. See my blogs of 11 Nov. 2011, 19 Feb. 2011, 21 Sept. 2010 and my website http://www.robert-w-jones.com/

Q7. What is consciousness?  A.  See my blog of 29 June 2011 and chapter 1 of my book Twelve Papers (available to download free on my website http://www.robert-w-jones.com/, Book).

Q8. Do we have free will?  A.  Depends upon your definition.  See my blog of 8 July 2011.

Q9. Does god exist?  A.  Such extraordinary beliefs would require extraordinary evidence.  No such evidence has been found.

Q10. What are human beings?  A.  Great apes

Q11. Does everything have a cause?  A.  Quantum mechanics says no.

A first course in plasma physics

I have taught a 1 credit introduction to plasma physics a few times and a 3 credit course a few times.  I have not found an introductory text book that I like so I have always taught the course from my own notes.  I have typically supplied printed handouts which cover perhaps as much as half of the course material.
It is not possible to cover everything that I might like in the 1 credit course.  My syllabus was typically:

1. particle balance, ambipolarity

2. energy balance and confinement time

3. the Debye length

4. the plasma frequency

5. Larmor orbits, cyclotron frequency, and cyclotron resonance heating

6. mean free path, crossections, collision frequency, diffusion, and diffusion across magnetic fields

7. fusion reactions, the Lawson conditions, breakeven, and ignition

8. particle drifts, EXB drift, grad B drift

9. magnetic mirrors (and the ionosphere)

10. closed magnetic systems, rotational transform, and equilibrium

11. plasma waves

12. minimum B and stability

Some of this follows my fusion energy review paper, J. Sing. Nat. Acad. Sci., 9, 71 (1980).
I am less sure what should be the coverage for a 3 credit course.  I have typically added things like:

13. A summary of the various plasma confinement systems and resulting fusion reactors. (Startng from something like J. R. Roth's review paper in IEEE Trans. on Plasma Science)

14. A summary of the various sorts of plasma sources. (Starting from something like my review paper in Physics Reports, Vol. 61, #5, June 1980)

15. Some discussion of plasmas in astrophysics.

16. A summary of plasma wave phenomena, instabilities, and their effect on plasma behavior and properties.

17. A discussion of various plasma diagnostics. (Starting from something like the chapter/paper on plasma diagnostics in my book "Twelve Papers" amazon # ASIN: B005SVVEYC)

18. (nonfusion) plasma applications and devices

You can't manage to cover all of these in a 3 credit course but I have picked from this list.

Doing (some) calculus without knowing calculus

It is common to have 2 "first year" physics courses.  One uses calculus, a "university physics" course, and one only uses algebra, a "college physics" course.  With physics enrollments lower than adminstrators would like there has been pressure to combine these into 1 single first year course.

Numerical methods allow at least some of the calculus to be done by students who only know algebra (plus some computer programming skills). The velocity component in the x direction is then the change in x devided by the time change, vx = dx/dt. The acceleration component in the x direction is then the change in vx devided by the time change, ax = d(vx)/dt.  One can then do integration on the computer with the simple assignment statements:

LET vx = vx + ax*dt

LET x = x + vx*dt

A simple planetary or satellite orbit program is then something like:

We can then explore elliptical orbits by increasing vy from 1 toward 1.414.

Beyond that we get parabolic and hyperbolic trajectories.            

Of course there are other issues with trying to make a single "size" course that would "fit" all students.  The lab component for one thing.                                                             

More people read your paper if it's rejected

I recall reading some years ago that scientific journal articles were read by such a small number of people that having your paper rejected (and resubmitted? once? twice?) actually resulted in more people reading it (as opposed to getting it accepted outright).  I have been unable to track down a reference to this but think it was based on the sort of analysis that de Solla Price used to do ("Little Science, Big Science")

Coding ideas

From studying neural networks (or logic circuits) we know that instead of training a single neural network with m inputs and n outputs one can train n separate networks each with only 1 output.  So, if we have a programming problem that requires n outputs and we don't know how to solve it we could start by trying to solve the coding task for just 1 of the required outputs.  If successful we could then try to work on other outputs. (Perhaps sticking to parallel processing?!)  We could also eventually try to connect the separate solutions if needed ("term sharing").

With the kind of vector representations I use in Asa H generalization can be accomplished by deleting less important (smaller?) vector components and reducing the dot product similarity measure required for categorization.  Specialization can be accomplished by adding vector components (during learning) and raising the similarity level needed for categorization.

(A category can be defined by specification of ranges over which each vector component (attribute) can vary.  It need not be defined by specification of the dot product alone. i.e., one can use other similarity measures, etc.)

Human values and gender

Human values aren't what they should be. (Being composed mainly of a small set of simple drives and aversions.)  But such as they are they appear to serve men a bit better than they do women.

For example: A woman should want the fittest man she can find.  Model Daisy Lowe, on the other hand, thinks that "You can always judge a man by his shoes."