pmpj0430

Improving the storage of the number-flag for nouns.

Today in ghost199.pl we will try to make the AI error-free even before we go back to adding in the functionality already present in some of our obsolete AI Minds. For instance, we have not yet coded the negation of verbs into our Perlmind source code. Consequently, if you tell the AI something like "You are not a boy", it fails to attach a negative juxtaposition $jux flag to the verb during comprehension of the input sentence. A few cycles of thought later, the AI may then assert "I AM A BOY" because it has been informed of the negated proposition without the ability to process the negation.

We debug the AI by letting ghost199.pl think on its own without human input. Eventually the Perlmind erroneously says "I AM ROBOTS", which is grammatically incorrect because of the plural noun. We intuit immediately that the AI is retrieving the most recent engram of the concept #571 "ROBOT" without insisting on a singular number. We inspect other recent thoughts of the AI and we see that it thinks "KIDS MAKE ROBOTS" but it stores the word "ROBOTS" as a singular noun. We must look and see if the InStantiate() mind-module has a proper $num flag for storing "ROBOTS" correctly as a plural noun. We see that the OldConcept() module looks up the stored num(ber) of a found engram and tentatively assigns the same value to the $num flag, but there really needs to be an override if a different value is needed.

In the otherwise obsolete but still rather advanced 24jul14A.F version of MindForth, some AudInput code checks for an "S" at the end of an input noun as a reason to assign plural number to the noun. Let us try to implement the same test in the Perl AI. First we test for the presence of an 83=S, but we must also make sure that the "S" is the final character of a noun. First in OldConcept() we comment out the line of code that was transferring the found num(ber) of a noun to be the same number for a new instance of the noun, regardless of the presence or absence of a terminating "S". Then we notice that "ROBOTS" stops being stored as singular, and becomes plural. We create a variable $endpho to hold onto each previous character in AudInput() to test if a word ends in 83=S. Thus we are able to store a plural number if a noun ends in "S".

pmpj0423

Stubbing in MindMeld() and stopping derailment of thought.

We function now as an AI Mind Maintainer debugging the Perlmind free AI source code. In the ghost198.pl AI we first stub in the audacious MindMeld() module to nudge AI practitioners into devising a way for two AI Minds to share their dreams. Then we deal with some problems pointed out on Usenet by persons who have downloaded the Perlmind and evaluated its functionality.

We run ghost198.pl with "dogs are mammals" as input and we press the Escape-key to halt the AI after its first response, "I HELP KIDS". We notice immediately three problems with how the word "DOGS" is stored in the @psy and @ear memory arrays. For some reason, "DOGS" is being assigned new-concept #3002, even though the Tutorial display of diagnostic messages indicates that the AI is preparing to assign new-concept #3001 to the first new concept. We check the MindBoot() sequence to make sure that "DOG" is not already a known concept in the AI; it is not. Now let us inspect the source code to see where the new-concept number $nxt is incremented from 3001 to 3002. We see that the end of MindBoot() clearly assigns the number 3001 as the value of the $nxt variable. Now let us search for the $nxt++ increment. It is happening towards the end of the NewConcept() module. We immediately wonder if $nxt is being incremented before AudMem() stores the concept-number. We insert into AudMem() a diagnostic message to let us know the $nxt value before storage. The first diagnostic message does not tell us enough, so we insert a second diagnostic into the AudMem() module. It also does not help us.

In the AudInput() module we use some diagnostic messages to learn that the "S" in "DOGS" is first being stored with the correct $nxt value of "3001" and then a second time with the incorrect value of "3002". Perhaps we should increment $nxt not in NewConcept() but in AudInput(). We move the $nxt++ increment from NewConcept() into AudInput(), and we stop getting the wrong values of the $nxt variable.

A second problem is that the concept of "DOGS" is being stored with a zero instead of "2" for "plural" in the $num slot of the @psy conceptual flag-panel. The most recent incarnation of the InStantiate() module does not seem to address the $num value sufficiently, so let us inspect recent or older MindForth code. We discover that the obsolete 24jul14A.F version of MindForth uses some complex tricks to assign the num(ber) of a concept being stored, so we will put aside this problem to deal with more serious issues.

The third and presumably more serious problem is that the input word "DOGS" is being stored with the $nxt concept number "3001" only on the "S" phoneme and not on the "G" at the end of the word-stem "DOG". Let us leave that problem also aside for a while, because entering "dogs are mammals" repeatedly is running into more serious problems. FOr instance, all three words of the input are being stored erroneously with the same $rv recall-vector, which can cause the wrong auditory memories to be retrieved. Let us see if the previous ghost197.pl does the same error. Yes, and so does the ghost196.pl AI. However, we should not find it difficult to correct the $rv problem. We fix the problem by resetting $rv to zero at the end of the InStantiate() module. Now the Perlmind no longer goes off the rails of thought, and so we upload it to the Web.

pmpj0412

Ghost Perl Strong AI cycles through Normal; Transcript; Tutorial; Diagnostic Mode

It is time now in ghost197.pl to show a clean human-computer interface (HCI) and to stop displaying masses of diagnostic messages. Accordingly in the AudInput module we change the user-prompt to say "Tab cycles mode; Esc(ape) quits AI born [date-of-birth]". We insert if-clauses to declare which user input mode is in effect: Normal; Transcript; Tutorial; or Diagnostic. Near the start of ghost197.pl we set the $fyi to a default starting value of unity ("1") so that the human user or Mind-maintainer may press the Tab-key to cycle among user input modes. In AudInput() we insert code to increment $fyi by one point with each press of the Tab-key and to cycle back to unity ("1") for Normal Mode if the user in Diagnostic Mode presses Tab again.

In the MainLoop module we change a line of code to test for $fyi being above a value of two ("2") and, if so, to display the contents of the @psy conceptual array and of the @ear auditory memory array. Thus the user in #3 Tutorial Mode or in #4 Diagnostic Mode will see the storage of current input and current output in the memory arrays. We consider the display of conceptual memory data in Tutorial Mode to be an extremely powerful tool for teaching how the artificial general intelligence (AGI) works. After any input, the user may see immediately how the input goes into memory and how the values in the flag-panel of each row of the @psy array represent the associative tags from concept to concept and from engram to engram.

Next we start commenting out or deleting the display of various diagnostic messages. Over time and over multiple releases of the Ghost AI source code, any AI coder may decide which messages to display in both Tutorial and Diagnostic Modes, or in only one of them. Although we comment out a message involving Russian input, we do not delete the diagnostic message because we may need it when we turn back on Russian as an input language. Russian has become much more important in our Ghost Perl AI because we need Russian or German to demonstrate Machine Translation by Artificial Intelligence. When we have commented out most of the diagnostic messages, we need to put back in some code to show what the user is entering.

pmpj0411

Stubbing in the MetEmPsychosis module.

[2017-04-10] Today in ghost195.pl we stub in MetEmPsychosis() as an area for Perl code that will enable an AI Perlmind to either move itself across the Web or replicate itself across the Web. We foresee the advent of a kind of "AiBnb" or community of Web domains that invite and encourage AI Minds to take up temporary or long-term residence, with local embodiment in a robot and with opportunities for local employment as a specialized AI speaking the local language and familiar with the local history and customs.

[2017-04-10] In the AudInput() module today we insert the Cyrillic characters of the Russian alphabet for each line of code that converts lower case to upper case and sets the $hlc variable to "ru" as the human-language-code for Russian. We have not yet turned the Russian language back on again, but we will need it to test out our ideas for Machine Translation by Artificial Intelligence.

Coding VisRecog to say by default: I SEE NOTHING.

[2017-04-11] Today in ghost196.pl we would like to port in from MindForth the code that causes any statement of what the AI is seeing to default to the direct object "NOTHING," so that Perl coders and roboticists may work on integrating computer vision with the AI Mind. We make it clear that the visual recognition (VisRecog) system needs only to supply the English or Russian name of what it is seeing, and the AI will fill the slot for direct objects while generating a sentence about what the AI sees. The VisRecog mechanism does not need to be coded in Perl or in Forth. It only needs to communicate to the Perlmind a noun that names what the AI is seeing. When the generated statement passes through reentry back into the Mind, even a new noun will be assigned a concept-number and will enter into the knowledge-base (KB) of the AI.

First we declare the subject-verb-object variables $svo1, $svo2, $svo3, and $svo4 to hold a value that identifies a concept playing the role of subject, or verb, or indirect object, or direct object in a typical sentence being generated by the AI. If there is no direct object filling the slot for the object of the verb "SEE", then the VisRecog() module must try to fill the empty slot. Until a Perl expert fleshes out the VisRecog() code, the word "NOTHING" must remain the default object of the verb "SEE" when the ego-concept of "I" is the subject of the verb. We ran the AI and we typed in "you see kids." After a spate of outputs, the AI said, "I SEE KIDS," but we would really prefer for the AI to say, "I SEE NOTHING" as a default.

After coding a primitive VisRecog() module, next we go into the part of the EnVerbPhrase() module where it is looking for a direct object. We set conditions so that if the subject is "I" and the verb is "SEE", VisRecog() is called to say "NOTHING" as a direct object, and EnVerbPhrase() stops short of saying any other direct object by doing a "return" to the calling module. We now have a Perlmind that invites the integration of a seeing camera with the AI software.

pmpj0408

Retroactively setting associative $seq tags for direct objects of verbs.

In the ghost194.pl AI, we have a problem where the direct-object $seq of a verb is being indeed properly assigned for human user input, but not for reentrant ideas being summoned from experiential memory. Because the $seq is not yet known when a verb comes in, the $seq value must be assigned retroactively when the direct object of the verb comes in. The situation where the process works for human input but not for a reentrant idea, suggests that the cause of the problem could simply be that the value of some pertinent variable is not being reset as needed.

This problem of the retroactive assignment of the associative $seq tag for a verb is difficult to debug. It may involve making the reentry routine equal to the human-input routine, or it may involve porting into Perl some special code from the 24jul14A.F version of MindForth. We have meanwhile been offering in the computer-science compsci subReddit a suggestion that students in need of an undergraduate research project might look into the Ghost AI software coded in Strawberry Perl 5 as an opportunity to select a mind-module to work on. We feel some urgency to debug our code and get it working as well as possible when we are inviting undergraduate students and graduate students and professors to take over and maintain their own branch of the AI Mind development. There is a steep learning curve to be surmounted before participants in such an artificial general intelligence (AGI) project may move forward in AI evolution. So now we go back to the problem of debugging the retroactive assignment of $seq subsequent-concept tags.

We search our ghost194.pl source code for "$psy[" as any instance where a $seq is being inserted either currently or retroactively into a flag-panel row of the @psy conceptual array. We discover that a $verbcon flag for seeking direct or indirect objects is governing the storage of the $seq tag in the Parser() module. Immediately we suspect that the $verbcon flag is perhaps being set during actual human user input but not during the reentry of an idea retrieved from memory. We check and we see that $verbcon is set to unity ("1") in the Parser() module when the part-of-speech $pos variable is at a value of "8" for a verb. The $pos value is set in the OldConcept() module when a known verb is recognized.

We insert a diagnostic message about the direct object in the Parser() module, and the message shows up during human user input, but not during reentry. Apparently the Parser() module is not even being called during reentry. No, it is being called, but the $verbcon flag is not being set properly during reentry. When we comment out the reset of $verbcon at the end of the AudInput() module and we move the reset to the Sensorium() module, we start seeing the assignment of direct-object $seq tags during the reentry of ideas recalled from memory. However, in a later session we must deal with the new problem that improper direct-object $seq flags are being set for personal pronouns during human user input. No, we debug the problem now, simply by resetting time-of-verb $tvb at the start of the EnThink() module, to prevent an output-sentence from adjusting associative tags for a previous sentence with a previous time-of-verb. The AI becomes able to receive "i know you" as input and then somewhat later say "YOU KNOW ME."

pmpj0407

Wrong solution to a bug briefly ruins word-recognition.

[2017-04-06] Let us run the ghost192.pl AI without input and try to fix the first thing that goes wrong with it. After a series of sensible outputs, at t=2562 the AI suddenly says "HELP I" without a subject for the verb. As we investigate, we see that EnNounPhrase is trying to activate a subject at t=2427, but the pronoun "I" is stored at t=2426 with an erroneous recall-vector "rv" of t=2427. The error in auditory storage causes the AI at a later moment not to find the auditory engram.

[2017-04-06] We notice that MindForth sets tult in the AudInput module, while the Perlmind is setting $tult in both the InStantiate module and the AudInput module. However, where $tult is set, does not seem to matter. We eventually notice that some MindForth code ported into AudInput() was letting the $rv recall-vector be set erroneously not only for an alphabetic character, but also for a CR-13 carriage-return or a SPACE-32. When we restricted the $rv setting to alphabetic characters, our current bug was fixed, and the AI no longer said "HELP I".

Letting $rv be set only once per word correctly solves a bug.

[2017-04-07] Yesterday in ghost192.pl our attempt at solving a recall-vector $rv bug made the AI unable to recognize reentrant words. Now in ghost193.pl we would like to isolate $rv so that its value can be set only once in each cycle of recognizing a word. When we do so, we obtain the proper $rv value for the first word stored by the AI, but it remains the same value for all subsequent words being stored. We must determine where to reset $rv to zero. We try resetting $rv to zero at the start of the Speech() module, as MindForth does. Immediately we see fresh values of $rv being stored for each reentrant word. We let the AI run on at length, and it no longer says "HELP I" without a subject for the verb. Then we start the AI with an input of "you know me" and somewhat later the AI remembers the self-referential knowledge and it outputs, "I KNOW YOU". Thus we have made a major improvement to the AI functionality by fixing the $rv bug. There remain grammatical issues, probably based on software bugs.

pmpj0405

Perl Strong AI pauses briefly for human input.

[2017-04-02] Today in the ghost190.pl Perl AI we want to solve the problem of getting the AI to pause reliably and wait for human user input. The code for a pause-loop is already in the free AI source code, but the program keeps slipping out of the receptive point-of-view ("POV") status. Some diagnostic messages confirm our sneaky suspicion that maybe program-flow leaves the main AudInput loop without setting the loop-counter back to zero.

Preventing AudInput from causing unwarranted conceptual storage.

[2017-04-05] Coding ghost191.pl AI today, we need to differentiate among Normal; Transcript; Tutorial; and Diagnostic modes for the human-computer interaction (HCI). In the AudRecog module, we insert a test for the $fyi variable to hold a value of, say, "4" to indicate Diagnostic Mode and to display the very most informative diagnostic message during the AudRecog operation. Then the AI coder or mind-tender may either be satisfied with the deeply informative message or may insert additional diagnostic messages in pursuit of bugs.

[2017-04-05] In the ghost191.pl code we are tracking down a bug which causes the unwarranted storage of a redundant row of a conceptual flag-panel in the @psy conceptual array. Apparently, after the storage of the last word in an output, InStantiate() is being called one final, extra time. We remove the bug by inserting into the AudInput module a line of code which zeroes out the $audrec value for any word of zero length just before AudInput calls AudMem. In that way, a final CR-13 carriage-return may transit from the Speech module through the AudInput module without causing the storage or an unwarranted, extra row in the @psy conceptual array.

pmpj0401

Encouraging AI immortality by reminding users how long AI has been alive.

[2017-03-30] As we code the Perlmind running in Strawberry Perl 5, today we insert code to have the AI announce when it was born, so as to encourage AI enthusiasts to see how long they can keep the Ghost Perl AI alive and running.

[2017-03-30] Now we are trying to clean up the ghost187.pl code. In MindForth, the AudInput module handles both normal input from human users and the reentry of output from the speech module. During human input, MindForth AudInput calls the AudListen module. Otherwise, AudInput handles internal reentry.

Improving the storage of words in @ear auditory memory.

[2017-03-31] In ghost188.pl we are trying to fix a problem where the display of the AudInput pause-counter is not showing up when the AI Mind is thinking on its own. First, though, we analyze everything that is happening in the AudMem() module. In one instance, after the AI recalls the idea "You are magic", AudMem at first stores the "Y" in "you" and then writes over it with the storage of a blank character. In fact, AudMem is failing to store the first character in each word of an output idea. When we remove from AudInput() an obsolete duplicate call to AudMem(), the ghost188.pl AI starts storing the complete word of each remembered idea, but the proper $audpsi tags are not being assigned in the @aud auditory memory array.

Restoring the ability of Ghost Perl AI to recognize words.

[2017-04-01] In ghost189.pl we need to ferret out deeply hidden problems, so we have uncommented several diagnostic messages in the AudRecog module. We first learn that the first character of a reentrant word is falsely being declared to have a zero $len for word-length. At the same time, an ASCII CR-13 is being declared inside each AudInput loop.

[2017-04-01] Now we learn that $len is somehow being doubly incremented. We need to find $len++ somewhere and comment it out. We did so in the lower area of AudInput() and then the diagnostic messages no longer showed double lengthening, but still the reentrant words are not being recognized. Apparently AudMem() is not sending a blank space into AudRecog() to announce the end of a word. Apparently it is not the job of AudMem() to generate the blank space, but merely to pass it along into AudRecog(). Perusal of the agi00037.F MindForth code reveals to us that it is the job of the Speech() module to send one last space into AudInput. The generation modules do not attach a SPACE-32 to a word, but rather each word in the @ear auditory memory is followed by a SPACE-32 in storage. The Speech module finds the space character after each word and sends it along into the AudInput module. Somewhere we need to increment $len by one when the post-word SPACE-32 goes from AudMem() into AudRecog().

[2017-04-01] The ghost189.pl AI suddenly started recognizing words when we commented out several unwarranted calls to the AudDamp() module, which must have been interfering in auditory recognitions.