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The psiDamp module plays a key role in
artificial
consciousness
by damping down the
activation of each mindcore concept
immediately after it has been thought as part of an idea,
so that consciousness may ride a
moving wave of active concepts
to flit from thought to thought in the stream of consciousness.
In the diagram above, Activate and psiDamp work to keep concepts
activated, while psiDecay gradually reduces the activation of all
concepts throughout the brain-mind. Whereas the Activate module
puts a strong activation on old concepts that are re-activated in
the course of recall and thinking, the psiDamp module lowers the
activation of each concept immediately after the concept has been
used in the generation of a thought. A virtual tug-of-war occurs
between psiDamp, trying to keep concepts activated, and psiDecay,
trying to lower the activation of all concepts in a natural fade.
If psiDecay did not work to lower conceptual activations, more and
more concepts would achieve a saturation-point of activation until
no chains of thought would stand out against the noisy background.
The psiDamp module slightly lowers the activation of a concept
after it has figured in a current thought, so that the concept may
briefly remain active enough to join a meandering chain of thought.
As the possible thoughts about a concept are exhausted, pdiDecay
removes the concept from conscious consideration until the next
time that the Activate module brings the concept back to life.
// psiDamp() is called from nounPhrase() or verbPhrase()
// to de-activate a concept that was briefly activated.
function psiDamp() { // ATM 21jun2002; or your ID & date.
// We use tov to avoid damping reentered thoughts.
for (i = tov; i>midway; --i) {
Psi[i].psiExam(); // cycle through recent Psi nodes
if (psi0==urpsi) Psi[i] = new psiNode(psi0,0,psi2,psi3,psi4,psi5,psi6);
} // end of backwards loop
} // psiDamp returns to nounPhrase, verbPhrase, etc.
\ psiDamp is called from nounPhrase or verbPhrase
\ to semi-activate a concept that was briefly activated.
: psiDamp ( reduce activation of a concept ) \ atm 23jan2006
\ 5 lump ! \ 8oct2005 Let Activate go higher than psiDamp does.
\ 10 lump ! \ 15oct2005 For sake of meandering chains of thought.
\ 30 lump ! \ 23jan2006 Upper-tier concept drops to top of lower tier.
fyi @ 2 > IF CR \ Too detailed for Tutorial mode.
." psiDamp called for urpsi = " urpsi @ .
." and lump = " lump @ .
THEN
midway @ 1 + t @ 1 + DO \ Loop backwards from t+1.
I 0 psi{ @ urpsi @ = IF \ If psi0 is found,
\ 0 I 1 psi{ ! THEN \ set activation psi1 to zero.
\ 2 I 1 psi{ ! THEN \ 29apr2005: Set to not-quite-zero.
lump @ I 1 psi{ ! THEN \ Set in psiDamp or in calling module.
-1 +LOOP \ End of backwards loop.
0 lump ! \ 15sep2005 safety measure
psiDecay \ 21sep2005 For the sake of the Moving Wave Algorithm.
\ If psiDecay is to be used sparingly, it is especially
\ warranted here, to act in concert with psiDamp.
\ psiDecay \ Against unresolved activations; favoring user inut.
; \ psiDamp returns to nounPhrase, verbPhrase, etc.
An AI Mind programmer will most likely need to troubleshoot
the psiDamp module in conjunction with other mind-modules.
One of the most helpful techniques for troubleshooting the
psiDamp module is to use a "caller" variable to display
which other module is calling psiDamp at any given time.
In the JavaScript tutorial AI mind, the "caller" variable
may simply carry the name of the calling module as a
text string, but in Forth the "caller" variable might be
used to carry a numeric identifier of the calling module.
Some versions of the original Mind.Forth may identify
calling modules by the AI4U page number of the chapter
on the particular module. For novel mind-modules, coders
may need to devise a novel numbering scheme.
5. psiDamp Resources for
Seed AI Germination and Evolution
Ask your local science museum if they have an AI Mind exhibit.
If they do not, volunteer to install
MindForth as an AI exhibit.
See which museum has the oldest living artificial intelligence.
The psiDamp module is listed on page 164
in your POD (print-on-demand)
AI4U textbook,
as worthily reviewed and intellectually evaluated
by Mr.
Christopher Doyon of the on-line Turing Store; and
by Prof.
Robert W. Jones of Emporia State University.
A
search on eBay may reveal offerings of AI4U and
a
catalog search for
hardbound and
paperback copies
may reveal libraries beyond the following where students
of artificial intelligence may borrow the AI4U textbook:
Texas A&M University
Consider
http://www.bookcrossing.com as a way to
circulate and track your wandering copy of AI4U.
At your own library you may submit a request for
the acquisition of AI4U with ISBN 0595654371.