MindForth Programming Journal (MFPJ) 2010 August 19
Thurs.19.AUG.2010 -- Discovering a Major
Problem
We are at a stage now where we may
home in on the goal of having the AI maintain a continuous
chain of self-referential thought.
We rename 17aug10A.F as 19aug10A.F and we run the AI
code in search of correctable glitches. When we notice
erroneous output like "WHO IS AM I", we go into the WhoBe
module and we reset the "mfnflag" variable to zero after
it causes the saying of "IS", so that the AI will stop
unwarrantedly inserting "IS".
Then we notice that stray conceptual activations are
carrying over even after KbTraversal is invoked, although
KbTraversal is supposed to heavily activate a particular
concept in a pre-ordained queue of activand concepts. So
at the start of KbTraversal we comment outthree mild calls
to PsiDecay, and we instead insert a call to the harsh
PsiClear module, so that only the designated activand
concept shall be activated. The problem of interference
from stray activations seems to go away.
Then we notice a major problem, worthy of focussing our
attention on for a major, upload-worthy update of the
MindForth AI. We notice that the AI properly activates the
concept of God during KbTraversal and properly asks the
resulting question "GOD WHO IS GOD", but the AI does not
remember our input of "God is Jesus" and repeats the
question "GOD WHO IS GOD" during KbTraversal, even though
a link from "GOD" to "JESUS" is still present in the
recent memory of the AI, as shown in some old engrams.
424 : 55 0 0 100 100 7 66 55 to WHO
427 : 66 0 2 55 55 8 100 66 to IS
431 : 100 39 1 66 55 5 66 100 to GOD
435 : 100 39 1 100 0 5 58 100 to GOD
438 : 58 23 2 100 100 8 111 58 to BE
444 : 111 0 2 58 100 5 0 111 to JESUS
450 : 111 0 2 111 0 5 55 111 to JESUS
454 : 55 0 0 111 111 7 66 55 to WHO
457 : 66 1 2 55 55 8 111 66 to IS
463 : 111 0 2 66 55 5 66 111 to JESUS
We suspect immediately that KbTraversal is reactivating
the "GOD" concept at an activation so low that the WhoBe
module gets called repeatedly for the low-activation "GOD"
concept, even though there is an engrammatic link
between "GOD" and "JESUS". No, KbTraversal sends a rather
high activation of sixty-two (62) into NounAct.
After the AI asks, "WHO IS GOD", the word "GOD" is left
with an activation of thirty-nine (39). That activation
should revive the "known" answer, namely that "GOD IS
JESUS". However, let us check what is the threshold
activation for invoking the WhoBe module. Oh, WhoBe is
called by AskUser when a be-verb activation is less than
forty (40). We could try gradually lowering the threshold
activation from "40" down towards thirty and lower. We
could also insert some diagnostic message code that will
reveal to us what real values within BeVerb are letting
AskUser call WhoBe.
If we solve this glitch properly so that the AI
initially asks a who-is question but thereinafter
remembers the answer supplied by the human user, we will
have a very powerful demonstration of cognitive ability on
the part of the AI. The testing of that ability will be
worthy of mention in the MindForth
user manual.
Thurs.19.AUG.2010 -- Novelty: Testing for Lowest
Maximum
Although BeVerb was testing "beact" for an activation
lower than forty (40) and we switched to testing for lower
than twelve (12), we still did not escape calling AskUser
and WhoBe, because one value of "beact" was "1" and
another value of "beact" was "14". Immediately we realized
that we need to test not for a single lowest value
of "beact", but for a lowest maximum value.
Fri.20.AUG.2010 -- Knowledge-Base Responses to Who-
Queries
In our coding yesterday we were able to isolate "maxbeact"
as a variable that would prevent calls from BeVerb to
AskUser and on to WhoBe if a single item of engrammatic
knowledge about a concept exceeded a threshold level,
while disregarding sub-maximum activations which would
have caused a call to WhoBe, and which did indeed cause a
call to WhoBe when the human user had not yet entered any
knowledge about the concept in question. Unfortunately,
calls to WhoBe were still getting through -- by way of the
legacy "recon" system for posing a what-query upon the
introduction of a previously unknown noun. Immediately we
found ourselves in a quandary, because the conflicting
decision-routines for "maxbeact" and for "recon" were
relying upon different levels of threshold activation. We
noticed yesterday that the EnCog (English thinking) module
in our Forth
code since 10 December 2009 has contained the comment-
remark that "recon" may soon be phased out. We do not
remember exactly why we were thinking of phasing
out "recon", but we see in retrospect that the "recon"
system was too indirect in its method of generating a
question about an unfamiliar noun. Although yesterday we
were daunted by the prospect of having to integrate
the "recon" system and the "maxbeact" system, today with
more clarity we realize that we need only to comment out
the central test of the "recon" value in order to permit
the "maxbeact" system to operate without interference from
the "recon" system. Then, if the unimpeded "maxbeact"
system works, in the sense of letting the AI initially ask
questions before knowledge is gained, and in the sense of
recalling the knowledge instead of asking unwarranted
questions, we may proceed to dismantle the
obsolete "recon" system in a careful, non-disruptive way.
So now we try to comment out the heart of the "recon"
system.
After commenting out the assignment of "recon" in the
VerbPhrase module, we no longer obtained "what-is"
questions about unfamiliar nouns, but we also did not
obtain factual answers to who-queries about knowledge that
had been entered about a previously mysterious noun.
Perhaps a threshold was still operating to prevent the
generation of a statement in response to a who-query from
the human user. Or perhaps not enough activation was going
into "spreading activation" by way of the NounAct module.
We decided to insert a diagnostic message at the start of
the NounAct module.
We are still not getting the knowledge back out.
Perhaps the competent threshold for the old "recon" system
is still preventing the formulation of a statement of
knowledge. Having knocked out the operation of "recon" as
a determinant in the BeVerb module, perhaps we should
either lower or eliminate the threshold used in
conjunction with "recon". In BeVerb, we are using a
threshold of "12" for "maxbeact", while in VerbPhrase the
threshold in connection with "recon" has long been set
at "20". We will comment out the "20" threshold in
VerbPhrase and see what happens with a much lower
threshold of "12" -- the same as with "maxbeact" --
although we seem to recall that the threshold of "20" was
chosen in order to prevent spurious statements of false
knowledge.
Ah, now we are getting somewhere, as the following
exchange shows.
Robot:
Human: god
Robot: GOD WHO IS GOD
Human: god is jesus
Robot: JESUS BE JESUS
Human: who is god
Robot: GOD BE JESUS
Human:
User Command: halt
Currently, the BeVerb module is set up to choose a proper
form of be-verb only for personal pronouns like "HE SHE
IT", etc. If we enhance the BeVerb module to let it find a
be-verb for a noun, we may start getting the proper
generation of knowledge-based responses to who-queries.
In the VerbPhrase module, we have a test which detects
the imminent selection of AM, IS or ARE and shunts the
continuation of the sentence-generation off to the BeVerb
module. Let us try adding the be-verb "BE" to the group of
verbs that will shunt generation off to the BeVerb module.
When we tried to use BeVerb to switch from "BE" to "IS"
in who-query responses, the AI failed to state the correct
predicate nominative, so we will comment out and release
our semi-successful code with a view to switching "BE"
to "IS" in a later release. Our
current code shows the AI at least finding the factual
knowledge for making an albeit grammatically awkward
response to a who-query.
