jmpj0922

JavaScript AgiMind understands and thinks with prepositions.

[2019-09-20] In the JavaScript AgiMind.html we are now trying to reproduce the new AGI functionality that we achieved a month ago in the ghost.pl Perlmind. The Ghost in the Machine became able to understand an input like "John writes books for money" and was able to respond properly to a query like "What does John write?"

When we enter "john writes books for money" and the AgiMind responds "WHAT ARE JOHN", it simply means that we need to add the noun "JOHN" to the innate vocabulary. So from the "perlmind.txt" we transfer "JOHN" as concept #504 into the JavaScript free AI source code, and now the AgiMind responds "STUDENTS READ BOOKS", which indicates that the AgiMind knows who or what John is, and what books are. But we also check the Diagnostic mode to make sure that the conceptual associative tags are being assigned properly. We are not sure, so we enter "what does john write" and we get a long response of nonsense.

[2019-09-21] In our second day, we discover that the ReEntry() module has been causing a reduplication of the output of the AgiMind. For troubleshooting, we temporarily disable the ReEntry module. Then we discover that some wrong associative tags are being assigned during human input. We run the ghost.pl AI to see how the correct associative tags are supposed to be assigned.

We discover that a line of InStantiate() code is assigning a false psi19 tpr value when only a zero value should be assigned. The false value being assigned is actually already there, so some other line of code must be assigning it earlier. But there is no earlier assignment, so the false tpr value is obviously being assigned retroactively -- which is something that any AI mind maintainer must learn to watch out for. Probably the retroactive assignment is happening in the EnParser() module, which does a lot of retroactive assignments because one word of human input may have an effect upon an earlier word of human input. Through substitution of "777" as a spurious value in the psi19 location of a snippet of assignment code in the EnParser() module, we discover which snippet is making the erroneous, non-777 assignment. Then through further substitution of "444" in the psi19 slot, we discover an earlier snippet of EnParser() code which is assigning a wrong value at the tvb time-of-verb time-point. So there must be an even earlier "tvb" snippet that is creating a spurious psi19 value. We discover that earlier snippet in the InStantiate() module. After much other coding, when we bring in a reset of tult to zero from the ghost.pl AI, we stop getting the spurious psi19 values.

[2019-09-22] In our third day, we run the ghost.pl AI that already works with prepositional phrases, and we discover that yesterday we trying to fix something that was not even a bug. The AgiMind was properly assigning the tpr tag to link the noun "BOOKS" to the preposition "FOR", and we mistakenly thought that the tag was supposed to be assigned also with "FOR". No, the preposition "FOR" needs only a tkb tag leading to "MONEY" as its object. Now we have gotten the tkb tag to be assigned properly for remembering the object of a preposition. After extensive debugging, we obtain the following exchange:

AI Mind version 22sep19A on Sun Sep 22 19:55:56 PDT 2019
Robot: I UNDERSTAND YOU
Human: john writes books for money

Robot: STUDENTS READ BOOKS
Human:

Robot:
Human: what does john write

Robot: JOHN WRITES BOOKS FOR MONEY

redux

Converting ancient Latin artificial intelligence into modern Russian AI.

The conversion of a JavaScript English-language AI into a Latin AI began on Thursday 2019-04-18 in April of 2019. Inspiration came from "Die Traumdeutung" where Sigmund Freud intones "Flectere si nequeo superos, Acheronta movebo." If one cannot bend the netgods of AI, move the mindset of Latin and Greek scholars.

A minor challenge in coding Mens Latina was the lack of an explicitly stated subject for many verbs in Latin, which occurs also in Russian. The solution was to skip three points in time-indexed memory to make room for the creation of a hidden concept to fill in for the unstated but understood subject of a verb.

Solving the AI-hard problem of the natural language understanding of a Latin or Russian sentence regardless of its syntactic word-order required waiting for the input of an entire clause before declaring subjects and objects on the basis of inflectional word-endings.

The conversion of artificial intelligence in Latin language into artificial intelligence in Russian language began yesterday on Friday 2019-05-24 in May of 2019.

jmpj1028

AI Mind uses EnPrep() to think with English prepositions.

In the JavaScript AI Mind we have a general goal right now of enabling the first working artificial intelligence to talk about itself, to learn about itself, and to achieve self-awareness as a form of artificial consciousness. Two days ago we began by asking the AI such questions as "who am i" and "who are you", and the AI gave intelligent answers, but the asking of "where are you" crashed the program and yielded a message of "Error on page" from JavaScript. It turns out that we had coded in the ability to deal with "where" as a question by calling the EnPrep English-preposition module, but we had created not even a stub of EnPrep. The AI software failed in its attempt to call EnPrep and the program halted. So we coded in a stub of EnPrep and now we must flesh out the stub with the mental machinery of letting flows of quasi-neuronal association converge upon the EnPrep module to activate and fetch a prepositional phrase like "in the computer" to answer questions like "where are you".

Our first and simplest impulse is to code in a search-loop that will find the currently most active preposition. Let us now write that code, just to start things happening. Now we have written the loop that searches for prepositions, but not for the most active one, because there are other factors to consider.

What we are really looking for, in response to "where are you" as a question, is a triple combination of the query-subject qv1psi and the query-verb qv2psi and a preposition tied with an associative pre-tag to the same verb and the same subject. We can not simply look for a subject and a verb linking forward to a preposition like in the phrase "to a preposition" or "in the computer", because our software currently links a verb only to its subject and to its indirect and direct objects, not to prepositions. Such an arrangement does not appear defective, because we can make the memory engram of the preposition itself do the work of making the preposition available for the generation or retrieval of a thought involving the preposition. We only need to make sure that our software will record any available pre-item so that a prepositional phrase in conceptual memory may be found again in the future. In a phrase like "the man in the street", for instance, the preposition "in" does not link backwards to a verb but rather to a noun. In this case, any verb involved is irrelevant. However, when we start out a sentence with "in this case", we have an unprecedented preposition, unless perhaps we assume that the prepositional phrase is associated with the general idea of the main verb of the sentence. For now, we may safely work with prepositions following a verb of being or of doing, so that we may ask the AI Mind questions like "where are you" or "where do you obtain ideas".

Practical problems arise immediately. In our backwards search through the lifelong experiential memory, it is easy to insist upon finding any preposition of location linked to a particular verb engrammed as the pre of the preposition. We may then need to do a secondary search that will link a found combination of verb-and-preposition with a particular qv1psi query-subject. The problem is, how to do both searches almost or completely simultaneously.

Since we are dealing with English subject-verb-object word order, we could let EnPrep() find the verb+preposition combination but not announce it until a subject-noun is found that has a tkb value the same as the search-index "i" that is the time of the query-verb. It might also help that the found subject must be in the dba=1 nominative case and must have the query-verb as a seq value, but the tkb alone may do the trick.

We coded in a test for any preposition with a quverb pre-tag, and we got the AI to alert us to the memory-time-point of "IN THE COMPUTER". Now we are assembling a second test in the same EnPrep() search-loop to find the qv2psi query-verb in close temporal proximity to the preposition.

We are using a new tselp variable for "time of selection of preposition", so we briefly shift our attention to describing the new variable in the Table of Variables. Now that we have found the verb preceding the preposition, next we need to implement the activation of the stored memory containing the preposition so that the AI Mind may use the stored memory to respond to "where are you" as a query. We may need to code a third if-clause into the EnPrep() backwards search to find and activate the qv1psi query-subject that is stored in collocation or close proximity to the query-verb and the selected preposition.

Now we have a problem. Since we let EnPrep() be called by the EnVerbPhrase() module, EnPrep() will not be called until a response is already being generated. We need to make sure that the incipient response accommodates EnPrep() by being the lead-up to a prepositional phrase. Perhaps we should not try to use verblock to steer a response that is already underway, but rather we should count on activation of concepts to guide the response.

Now let us try to use SpreadAct() to govern the response. After much coding, we got the AI to respond

IN COMPUTER I AM IN COMPUTER
IN COMPUTER I AM HERE IN COMPUTER

but there must somewhere be a duplicate call to EnPrep(). We eliminate the call from the Indicative() mind-module and then we get both an unwanted response and a wanted response.

YOU ARE A MAGIC IN A COMPUTER
I AM IN A COMPUTER

Obviously the AI is not responding immediately to our "where are you" query but is instead joining an unrelated idea with the prepositional phrase. Upshot: By having SpreadAct() impose a heftier activation on the qv1psi subject of the where-are-you query, we got the AI to not speak the unrelated idea and to respond simply "I AM IN A COMPUTER". Now we need to tidy up the code and decide where to reset the variables.

jmpj1011

JavaScript AI Mind uses EnVerbGen() for English verb-form inflections.

The JavaScript tutorial version of the first working artificial intelligence is becoming more sophisticated than ever. With roughly fifty mind-modules, the Strong AI advances the State of the Art first in one area, and then serendipitously in another area. For instance, the ability of the AI Mind to engage in automated reasoning with logical inference leads to a question-and-answer session between human minds and their incipient overlords, i.e., the current archetypes of the future Artificial Super-Intelligence (ASI). When the human user has confirmed or negated an inferred conclusion from the InFererence() module, the AI assigns a heightened truth-value to the positive or negative knowledge remaining in the AI memory. Then the AI states the new knowledge in its positive or negative formulation. A negated inference comes out something like "GOD DOES NOT PLAY DICE". A validated inference becomes a simple declarative sentence like "JOHNNY READS BOOKS", which requires the AI Mind to choose the correct form of the verb "read".

Because we code the first working artificial intelligence not only in English but also in Russian, we found it necessary several years ago to create the RuVerbGen() module for Russian verb-generation. When the ghost.pl AI cannot find a needed Russian verb-form, it simply cobbles one together from the stem of the Russian verb and the inflectional endings which complete a Russian verb. We avoided this problem in English for the last six years by simply ignoring it, but now the AI Mind needs to imitate the RuVerbGen() module with the EnVerbGen() module for English verb-generation. Just to change "God does not play dice" to "God plays dice" requires attaching an inflectional "S" to the stem or the infinitive form of the verb "play". As we code the EnVerbGen() module based on grammatical parameters, we encounter problems because the software needs to know the grammatical person and the grammatical number of the subject of an inferred idea in order to think a thought like "God plays dice" or "Johnny reads books".

Because the InFerence() module has not been storing the grammatical number of the English noun serving as the subject of a silent inference, our brand-new EnVerbGen() module has not been able to generate the third-person singular verb-form necessary for stating a validated inference like "Johnny reads books" or "Fortune favors fools" -- which was originally "Fortuna favet fatuis" in Latin. The artificial general intelligence (AGI) has become so sophisticated in its resemblance to human thinking that we need to change the InFerence() module to accommodate the requirements of the EnVerbGen() module.

We make the necessary changes and we code EnVerbGen() to deal not with Russian but with English verbs. We see a sample dialog between the AI and the human user.

Human: andru is professor
Robot: DOES ANDRU TEACH STUDENTS
Human: yes
Robot: THE ANDRU TEACHES THE STUDENTS
Human:
Robot: STUDENTS READ BOOKS

jmpj0921

Improving auditory recognition of singular and plural noun-forms.

The JavaScript Artificial Intelligence (JSAI) is currently able to recognize the word "book" in the singular number but not "books" in the plural number. It is because the AudRecog() mind-module is not recognizing the stem "book" within the inflected word "books". To correct the situation, we must first update the AudMem() module so that it will impose an audpsi tag not only on the final "S" in a plural English noun being stored, but also one space back on the final character or letter of the stem of the noun.

We copy the pertinent code from the AudMem() module in the ghost.pl Perl AI and the JavaScript AI begins to store the stem-tag, but only when the inflected word is recognized so that AudRecog() produces an audpsi recognition-tag.

Now we have a problem because the AI is keeping the audpsi of "800" for "IS" and attaching it mistakenly to the next word being stored by the AudMem() module. We fix the problem.

Next we implement the Imperative() module to enable the AI Mind to order any nearby human user: "TEACH ME SOMETHING."

jmpj0906

Improving EnArticle mind-module in first working artificial intelligence

The JavaScript artificial intelligence (JSAI) is not reliably transferring the usx values from InStantiate() to the EnArticle() module for inserting an English article into a thought, so we must debug the first working artificial intelligence in troubleshooting mode. We quickly see that the EnNounPhrase() module is calling EnArticle() for direct objects but not for all nouns in general. We also notice that we need to have EnNounPhrase() transfer the usx value.

We encounter and fix some other problems where the nphrnum value is not being set, as required for EnArticle() to decide between using "a" or "the".

Although we get the usx value to be transferred to the us1 value, we need a way to test usx not against a simultaneous value of us1 but rather against a recent value of us1. One solution may be to delay the transfer of usx by first testing in the EnArticle() module for equality between usx and us1 before we actually pass the noun-concept value of usx to us1. In that way, we will be testing usx against old, i.e., recent, values of the us1- us7 variables and not against the current value, which would automatically be equal. Then after the test for equality, we pass the actual, current value of usx.

We now have a JavaScript AI that works even better than the ghost.pl AI in Perl -- until we update the Perl AI. The JSAI now uses "a" or "the" rather sensibly, except when it now says "YOU ARE A MAGIC", because the default article for a non-plural noun is the indefinite article "a". Btw (by the way), today at a Starbucks store in Seattle WA USA we bought a green Starbucks gift card that says "You'Re MagicAL", because it reminds us of a similar idea in the AI MindBoot() sequence.

jmpj0616

Fleshing out VisRecog() in the First Working AGI

In today's 16may18A.html version of the tutorial AI Mind in JavaScript for Microsoft Internet Explorer (MSIE), we flesh out the previously stubbed-in VisRecog() module for visual recognition. The AGI already contains code to make the EnVerbPhrase() module call VisRecog() if the AI Mind is using its ego-concept and trying to tell us what it sees. As a test we input "you see god" and we wait for the thinking software to cycle through its available ideas and come back upon the idea that we communicated to it. As we explain in our MindGrid diagram on GitHub, each input idea goes into neuronal inhibition and resurfaces in what is perhaps AI consciousness only after the inhibition has subsided. Although we tell the AI that it sees God, the AI has no robot body and so it can not see anything. It eventually says "I SEE NOTHING" because the default direct object provided by VisRecog() is 760=NOTHING. In the MindBoot() sequence we add "I NEED A BODY" as an innate idea, so as to encourage users to implement the AI Mind in a robot. Once the AI has embodiment in a robot, the VisRecog() module will enable the AI to tell us what it sees.

jmpj0612

AI Mind Maintainer solves negation-of-thought problems.

In today's 12jun18A.html version of the JavaScript AI Mind for Microsoft Internet Explorer (MSIE), we find a negation-bug when we test the InFerence() module by inputting "anna is a woman". The AI then asks us, "DOES ANNA HAVE CHILD" and we answer "no" to test the AI. The AI properly states the idea negated by KbRetro() in the knowledge base, namely "ANNA DOES NOT HAVE CHILD". However, the negation-flag negjux for thought generation remains erroneously set to "250" for the 250=NOT adverb. We discover that the negjux flag, each time after serving its purpose, has to have a zero-reset in two locations, one for any form of the verb "to be" and another for non-be-verbs. We make the correction, and we finish off the negation-bug by resetting the tbev time-of-verb to zero at the end of OldConcept().

jmpj0611

Granting AI user-input priority over internal chains of thought.

We expect the AI Mind to activate incoming concepts mentioned during user input, so that the AI can talk to us about things we mention. Recently, however, the SpreadAct() module has been putting quasi-neural activation only on concepts thought about internally but not mentioned during user input. We need a way to let user-input override any activation being imposed by the SpreadAct() module for internal chains of thought, so that external input takes precedence. One method might be to use the quiet variable and set it to "false" not only during user input but also until the end of the first AI output made in response to user input. In that way, any concept mentioned by the user could briefly hold a high activation-level not superseded by the machinations of the SpreadAct() module for spreading activation. We implement the algorithm, and the AI then responds properly to user input. We solve some other problems, such as KbRetro() interfering with the conceptual engrams of an inference, and negation not being stored properly for negated ideas.

jmpj0605

Mentifex re-organizes the Strong AI SpreadAct() module.

In the 5jun18A.html JavaScript AI Mind we would like to re-organize the SpreadAct() mind-module for spreading activation. It should have special cases at the top and default normal operation at the bottom. The special cases include responding to what-queries and what-think queries, such as "what do you think". Whereas JavaScript lets you escape from a loop with the "break" statement, JavaScript also lets you escape from a subroutine or mind-module with the "return" statement that causes program-flow to abandon the rest of the mind-module code and return to the supervenient module. So in SpreadAct() we may put the special-test cases at the top and with the inclusion of a "return" statement so that program-flow will execute the special test and then return immediately to the calling module without executing the rest of SpreadAct().

When we run the JSAI without input, we notice that at first a chain of thought ensues based solely on conceptual activations and without making use of the SpreadAct() module. The AI says, "I HELP KIDS" and then "KIDS MAKE ROBOTS" and "ROBOTS NEED ME". As AI Mind maintainers we would like to make sure that SpreadAct() gets called to maintain chains of thought, not only so that the AI keeps on thinking but also so that the maturing AI Mind will gradually become able to follow chains of thought in all available directions, not just from direct objects to related ideas but also backwards from direct objects to related subjects or from verbs to related subjects and objects.

In the EnNounPhrase() module we insert a line of code to turn each direct object into an actpsior concept-to-be-activated in the default operation at the bottom of the SpreadAct() module. We observe that the artificial Mind begins to follow associative chains of thought much more reliably than before, when only haphazard activation was operating. In the special test-cases of the SpreadAct() module we insert the "return" statement in order to perform only the special case and to skip the treatment of a direct object as a point of departure into a chain of thought. Then we observe something strange when we ask the AI "what do you think", after the initial output of "I HELP KIDS". The AI responds to our query with "I THINK THAT KIDS MAKE ROBOTS", which is the idea engendered by the initial thought of "I HELP KIDS" where "KIDS" as a direct object becomes the actpsi going into SpreadAct(). So the beastie really is telling us what is currently on its mind, whereas previously it would answer, "I THINK THAT I AM A PERSON". When we delay entering our question a little, the AI responds "I THINK THAT ROBOTS NEED ME".

jmpj0603

AI Mind spares Indicative() and improves SpreadAct() mind-module.

We have a problem where the AI Mind is calling Indicative() two times in a row for no good reason. After a what-think query, the AI is supposed to call Indicative() a first time, then ConJoin(), and then Indicative() again. We could make the governance depend upon either the 840=THINK verb or upon the conj-flag from the ConJoin() module, which, however, is not set positive until control flows the first time through the Indicative() module. Although we have been setting conj back to zero at the end of ConJoin(), we could delay the resetting in order to use conjas a control-flag for whether or not to generate thought-clauses joined by one or more conjunctions. Such a method shifts the problem back to the ConJoin() module, which will probable have to check conceptual memory for how many ideas have high activation above a certain threshold for warranting the use of a conjunction. Accordingly we go into the Table of Variables webpage and we write a description of conj as a two-purpose variable. Then we need to decide where to reset conj back to zero, if not at the end of Indicative(). We move the zero-reset of conjfrom ConJoin() to the EnThink() module, and we stop getting more than one call to Indicative() in normal circumstances. However, when we input a what-query, which sets the whatcon variable to a positive one, we encounter problems.

Suddenly it looks as though answers to a what-think query have been coming not from SpreadAct(), but simply from the activation of the 840=THINK concept. It turns out that a line of "psyExam" code was missing from a SpreadAct() search-loop, with the result that no engrams were being found or activated -- which activation is the main job of the SpreadAct() module.

jmpj0530

Solving who-query problems and EnParser bug.

Although the ghost.pl AI responds to a who-query by calling SpreadAct() from the end of AudInput(), the JSAI will call SpreadAct() too many times from AudInput() before the end of the input. Since we need to test for qucon when the Volition() module is not engaged in thinking, we test for quconin the Sensorium() module, which does not call AudInput() but which is called from the MainLoop() after each generation of a thought.

We must also troubleshoot why the JSAI eventually outputs "ME ME ME". We discover that EnNounPhrase() is sending an aud=726 into Speech() while there is a false verblock=727. Then we learn that the concept-row at the end of "ROBOTS NEED ME" for "ME" at t=727 has an unwarranted tkb psi13=727, as if the concept 701=I had a tkb. Apparently we need to prevent a false tkb from being stored. An inspection of the diagnostic display shows that the tkb properly set for each verb is improperly being retained and set for the object of the verb. We then notice that the EnParser() module is properly setting the time-of-direct-object "tdo" to be the tkb of a verb and leaving the tkb value set to the "tdo" value. So we insert into EnParser() a line of code to reset tkb immediately back to zero after storing the tkb of a verb, and the erroneous "ME ME ME" output no longer appears.

jmpj0525

Preventing wrong grammatical number for a predicate nominative.

In the 25may18A.html version of the JavaScript AI Mind we wish to correct a problem where the AI erroneously says "I AM A ROBOTS". The wrong grammatical number for "ROBOT" results when the AI software is searching backwards through time for the concept of "ROBOT" and finds an engram in the plural number. We hope to fix the problem by requiring that the EnVerbPhrase() module, before fetching the predicate nominative of an intransitive verb of being, shall set the "REQuired NUMber" numreq variable to the same value as the number of the subject of the be-verb, so that the EnNounPhrase() module may find the right concept for the predicate nominative and then also find (or create) the English word of the concept with the proper inflectional ending for the required number. Since the numreq value shall be of service during one pass through the EnNounPhrase() module, we may safely zero out the numreq value at the end of EnNounPhrase().

jmpj0522

Expanding MindBoot with concepts to demonstrate AI functionality.

Today in the 22may18A.html version of the AI Mind in JavaScript (JSAI) for Microsoft Internet Explorer (MSIE), we wish to expand the MindBoot() module with a few English words and concepts necessary for the demonstration of the AI functionality. We first create a concept of "ANNA" as a woman, for two or three reasons. Firstly, we want the JSAI to be able to demonstrate automated reasoning with logical inference, and the MindBoot() sequence already contains the idea or premise that "Women have a child". Having created the Anna-concept, we typed in "anna is a woman" and the AI asked us, "DOES ANNA HAVE CHILD". If the concept of Anna were not yet known to the AI, we might instead get a query of "WHAT IS ANNA". Secondly, we want "Anna" as a name that works equally well in English or in Russian, because we may install the Russian language in the JSAI. In fact, we go beyond the mere concept of "Anna" and we insert the full sentence "ANNA SPEAKS RUSSIAN" into the MindBoot so that the AI knows something about Anna. We create 569=RUSSIAN for the Russian language, so that later we may have 169=RUSSIAN as an adjective. When we type in "you speak russian", eventually the AI outputs "I SPEAK RUSSIAN". A third reason why we install the concept 502=ANNA is for the sake of machine translation, in case we add the Russian language to the JSAI.

Next to the MindBoot() sequence we add "GOD DOES NOT PLAY DICE" in order to demonstrate negation of ideas and the use of the truth value, because we may safely assert in the AI Mind the famous Einsteinian claim about God and the universe. We type in "you know god" and the Ai responds "GOD DOES NOT PLAY DICE". Let us try "you know anna". The AI responds "ANNA SPEAKS RUSSIAN". Next we add the preposition "ABOUT" to the MindBoot so that we may ask the AI what it thinks about something or what it knows about something. We are trying to create a ruminating AI Mind that somewhat consciously thinks about its own existence and tries to communicate with the outside world.

jmpj0520

Slowing down the speed of thought to wait for human input.

The biggest complaint about the JavaScript Artificial Intelligence (JSAI) recently is that the AI output keeps changing faster than the user can reply. Therefore we need to introduce a delay to slow down the AI and let the human user enter a message. In the AudListen() module we insert a line of code to reset the rsvp variable to an arbitrary value of two thousand (2000) whenever a key of input is pressed. In the English-thinking EnThink() module we insert a delay loop to slow the AI Mind down during user input and to speed the AI up in the prolonged absence of user input.

jmpj0513

Answering of what-think queries with a compound sentence.

We would like our JavaScript Artificial Intelligence (JSAI) to be able to answer queries in the format of "What do you think?" or "What do you know?" We begin in the InStantiate() module by zeroing out the input of a 781=WHAT concept by adding a line of code borrowed from the ghost.pl AI. Then we input "what do kids make" and the AI correctly answers, "KIDS MAKE ROBOTS". However, when we input "what do you think" or "what do you know", the AI does not respond with "I THINK..." or "I KNOW...". Therefore we need to make use of the Indicative() module to generate a compound sentence to be conjoined with the conjunction "THAT". Into the MindBoot() vocabulary we add an entry for the conjunction 310=THAT.

After much trial and error we have gotten the JSAI to respond to the query "what do you think" with "I THINK THAT I AM A PERSON". We let the English-thinking EnThink() module call the Indicative() module first for a main clause with the conjunction "that" and again to generate a subordinate clause. When we ask, "what do i think", the response is "YOU THINK THAT I AM A PERSON". When we inquire "what does god think", the ignorance of the AI engenders the answer "I THINK THAT GOD THINK" which may or may not be a default resort to the ego-concept of self.

jmpj0317

Restoring JavaScript variable-comments and removing obsolete variables.

Since we assume that many people have made copies of the JavaScript Artificial Intelligence (JSAI) in order to study it, today we carefully make some pressing changes and for each change we provide an explanation by way of justification. First we delete some previously commented-out code-lines which were left in the open-source AI codebase for the sake of continuity, that is, to show that the particular lines of code were on the way out. Thus we remove the commented-out variable "kbyn" from 30jun2011.

Next from the obsolete 20mar07A version of the JSAI we restore comments for some variables and we remove some obsolete variables. We add a link to Consciousness above the Control Panel.

Anyone finding a bug in the AI software may subscribe to the mail-list agi@listbox.com for Artificial General Intelligence (AGI) and report bugs to the AGI community or engage in archived AGI discussion. There is no bug-bounty, other than the glory of the deed.

jmpj0302

Moving the JavaScript AI towards Artificial Consciousness

Two important goals for the AI Mind in JavaScript are the already demonstrated Natural Language Understanding (NLU) and the not-yet-proven Artificial Consciousness. Before we work explicitly on consciousness, we remove the clutter of some obsolete tutorial display code from the MainLoop and elsewhere, so that the program as a whole may be easier to understand and work with.

We have a chance here to demonstrate an entity aware of itself and of some other entity such as a human user conversing with the AI. If we start claiming that our JSAI has consciousness, Netizens will test the AI in various ways, such as asking it a lot of questions. Typical questions to test consciousness would be "who are you" and "who am i". The interrogative pronoun "who" sets the qucon flag to a positive value of one so that the SpreadAct module may activate the necessary concepts for a proper response. We need a way to make the AI concentrate on the subject of any who-query, so that the AI will give evidence of consciousness simply by answering the question.

When we enter "god is person" and then we ask, "who is god", the AI answers "GOD AM A PERSON" -- which sounds wrong but which only requires an improvement in finding the correct form "IS" for the verb "BE".

jmpj0120

MsIeAI for AI Mind Maintainers achieves albeit buggy sentience.

In the all-but-Singularity MsIeAI, alert-boxes have helped us to chase an elusive bug into the latter part of EnNounPhrase, where the AI is testing mjact for too low an activation. No, another alert-box tells us that we are back in EnVerbPhrase from EnNounPhrase before the "Error on page" flashes quickly. So at the end of EnVerbPhrase we insert a BUG-CHASE alert-box -- and the program never reaches it! So is the fatal bug somewhere just before the end of EnVerbPhrase()? Since that code contains a prepgen test, we modify an alert-box to reveal the prepgen value, but the alert-box fails to pop up. Then we check the declarations of variables at the top of the program, and prepgen is not there. Next we get prepgen from the ghost.pl AI and we drop it mutatis mutandis into the MsIeAI code. We are about to run the hopefully Next Big Thing AI and see what happens. Huh?!! Some kind of thought-storm is occurring. Shades of Watson! Come here! I need you!. And where is IBM Watson in our hour of need?

Now let us comment out the alert-boxes and see if the Watsonized AI will loop endlessly ad infinitum. Oh gee, this AI is still all messed up, but at least it is looping.

jmpj0613

JavaScript Mind Programming Journal (JMPJ) -- Saturday, June 13, 2015

These notes record the coding of the English tutorial AiMind.html in JavaScript for Microsoft Internet Explorer (MSIE).

Sat.13.JUN.2015 -- Troubles with InFerence in JavaScript

When we run the JavaScript AiMind.html in English and we try to show a Transcript of automated reasoning with logical InFerence, the Strong AI does indeed make an inference, but the dialog with the AI reveals that the AiMind program is failing to use some correct forms of verbs and personal pronouns. The thinking of the AI is correct and logical, but some mistakes are occurring in the expression of logical thought in proper English.

We suspect that grammatical errors are creeping in because the mind-modules related to inference are composing a sentence of thought outside of the normal routines of strictly grammatical English. We may be able to build up the same formalisms of strict grammaticality inside the inferential routines. For correct verb forms, however, we may need to start using the modules of OutBuffer and VerbGen.

Sat.13.JUN.2015 -- Troubleshooting the InFerence process

We notice that the AskUser module of the 14apr13A JSAI simply looks for the "quverb" query-verb to recall and speak, apparently without forcing the verb into the proper grammatical form, which is typically an infinitive form when a question is being asked with "DO" or "DOES" as an auxiliary verb. We should also check the Forth code and see if AskUser in MindForth has anything more advanced. Oh, the Forth code actually does test for a plural form to be used as if it were an infinitive.

The JSAI AskUser module looks for the "quobj" query-object without bothering to ensure that it will be an accusative form. The MindForth AskUser module also does not bother to check for an accusative case in the "quobj" word, so both the JavaScript AI and the MindForth AI need to be improved. The German Forth AI Wotan also seems to need improvement for grammatical forms in the AskUser module.

Mon.15.JUN.2015 -- Selecting Objects in Accusative

Now we have partially fixed the problem of ungrammatical English by inserting code into the AskUser() module to require the direct object or query-object to be in the accusative case. Instead of asking a question like "Does Mark need I?" the AI now asks, "Does Mark need me?"

However, when we answer "no" to the foregoing quesion, the AI eventually gets around to saying, "MARK DOES NOT NEEDS ME", because the AskUser() module is not insisting upon finding an infinitive form of the query-verb.

Table of Contents (TOC)

• Sat.13.JUN.2015 -- Troubles with InFerence in JavaScript

• Sat.13.JUN.2015 -- Troubleshooting the InFerence process

• Mon.15.JUN.2015 -- Selecting Objects in Accusative