pmpj0919

Students may teach the first working artificial intelligence.

In the ghost274.pl version of the Perlmind AI, we are having not Volition() but rather EnThink() call the Imperative() module to blurt out the command "TEACH ME SOMETHING". We are also trying to have Imperative() be the only module that sounds a beep for the human user, for several reasons. Although we were having the AskUser() module sound a beep to alert the user to the asking of a question, a beep can be very annoying. It is better to reserve the beep or "bell" sound for a special situation, namely the time when there has been no human input for an arbitrary period as chosen by the AI Mind maintainer and when we wish to let the Ghost in the Machine call out for some attention.

We are also eager for Netizens to set the potentially immortal ghost.pl AI running for long periods of time, both as a background process on a desktop computer or a server, and as part of a competition to see who can have the longest running AI Mind.

If a high school or college computer lab has the ghost.pl AI running on a machine off in the corner while the students are tending to other matters, a sudden beep from the AI Mind may cause students or visitors to step over to the AI and see what it wants. "TEACH ME SOMETHING" is a very neutral command, not at all like, "Shall we play a game? How about GLOBAL THERMONUCLEAR WAR?"

The teacher or professor could let any student respond to the beep by adding to the knowledge base of the AI Mind. Of course, clever students with a knowledge of Perl could put the AI Mind out on the Web for any and all visitors to interact with.

pmpj0916

Auditory recognition in the first working artificial intelligence

In the AudRecog() module of the ghost.pl free AI software, we need to figure out why a plural English noun like 540=BOOKS is not being stored with an $audpsi tag of 540 both after the stem of "book" and after the end of "books". The stem of any word stored in auditory memory needs an $audpsi tag so that a new input of the word in the future will be recognized and will activate the same underlying concept.

In AudMem() we have added some code that detects a final "S" on a word and stores the $audpsi concept number both at the end of the word in auditory memory, and also one row back in the @ear auditory array, in case the "S" is an inflectional ending. We leave for later the detection of "-ES" as an inflectional ending, as in "TEACHES" or "BEACHES".

In AudRecog() we tweak some code involving the $prc tag for provisional recognition, and the first working artificial intelligence in Perl does a better job at recognizing both singular and plural forms of the same word representing the same concept.

pmpj0912

Ask the first working artificial intelligence what it thinks.

Houston, we have a problem. The ghost.pl AI Mind in freely available -- download it now -- Strawberry Perl Five -- is not properly answering the question of "what do you think". The JSAI (JavaScript Artificial Intelligence) easily answers the same question with "I THINK THAT I HELP KIDS". So what is the Perl AI doing wrong that the JavaScript AI is doing right?

The problem seems to lie in the SpreadAct() module. We notice one potential problem right away. SpreadAct() in Perl is still using "$t-12" as a rough approximation for when to start a backwards search for previous knowledge about the subject-noun $qv1psi of a what-query, whereas the JSAI uses the more exact $tpu for the same search. So let us start using the penultimate time $tpu, which excludes the current-most input, and see if there is any improvement. There is no improvement, so we test further for both $qvipsi and $qv2psi, which are the subject-noun and the associated verb conveyed in the what-query.

SpreadAct() easily responds correctly to what-queries for which there is an answer ready in the knowledge base (KB), such as "I AM A PERSON" in response to "what are you". However, when we ask "what think you" or "what do you think", there is no pre-set answer, and the AI is supposed to generate a response starting with "I THINK" followed by the conjunction "that" and a statement of whatever the AI Mind is currently thinking.

From diagnostic messages we learn that program-flow is not quickly transiting from SpreadAct() to EnThink(). The AI must be searching through the entire MindBoot() sequence and not finding any matches. When the program-flow does indeed pass through EnThink() to Indicative() to EnNounPhrase(), there are no pre-set subjects or verbs, but rather there are concepts highly activated by the SpreadAct() module. So EnNounPhrase() must find the highly activated pronoun 701=I in order to start the sentence "I THINK..." in response to "what do you think".

Now we discover that the JavaScript version of EnNounPhrase() has special code for a topical response to "what-think" queries. In the course of AI evolution, it may be time now to go beyond such a hard-coded response and instead to let the activated "think" concept play its unsteered, unpredetermined role, which will happen not in EnNounPhrase() but in EnVerbPhrase().

It is possible that EnNounPhrase() finds the activated subject 701=I but then unwarrantedly calls the SpreadAct() module. However, it turns out that EnVerbPhrase() is making the unwarranted call to the SpreadAct() module, which we now prevent by letting it proceed only if there is no what-query being processed as evidenced by a $whatcon flag set to zero.

The early part of EnVerbPhrase() in the JavaScript AI has some special code for dealing with "what-think" queries. In the ghost.pl AI, let us try to insert some similar code but without it being geared specifically to the verb "think". We would like to enable responses to any generic verb of having an idea, such as "think" or "know" or "fear" or "imagine" or "suspect" and so forth.

By bringing some code from the JavaScript EnVerbPhrase() into the Perl EnVerbPhrase, but with slight changes in favor of generality, we get the ghost.pl AI to respond "I THINK". Next we need to generate the conjunction "that". But first let us remark that the AI also says "I KNOW" when we ask it "what do you know", so the attempt at generality is paying off. Let us try "what do you suspect". It even says "I SUSPECT". It also works with "what do you fear". We ask it "what do you suppose" and it answers "I SUPPOSE".

We still have a problem, Houston, because EnVerbPhrase() is calling EnNounPhrase() for a direct object instead of returning to Indicative() as a prelude to calling the ConJoin() module to say "I THINK THAT...." We set up some conditional testing to end that problem.

mfpj0907

Updating the EnArticle module for inserting English articles.

Today we update the EnArticle module for English articles in the MindForth first working artificial intelligence. We previously did the update somewhat unsatisfactorily in the ghost.pl AI in Perl, and then much more successfully in the tutorial JavaScript AI. We anticipate no problems in the MindForth update. As an initial test, we enter "you have a book" and after much unrelated thinking, the AI outputs "I HAVE BOOK" without inserting an article.

We trigger an inference by entering "anna is woman". In broken English, the AskUser module responds, "DO ANNA HAS THE CHILD", which lets us see that EnArticle has been called. We reply "no". MindForth opines, "ANNA DOES NOT HAVE CHILD".

We discover that the EnNounPhrase module of recent versions has not been calling the EnArticle module, so we correct that situation. We also notice that the input of a noun and its transit through InStantiate do not involve a call to EnArticle, so we insert into InStantiate some code to make EnArticle aware of the noun being encountered.

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.

pmpj0903

Upstream variables make EnArticle insert the definite article.

We attempt now to code the proper use of the definite English article "the" in a conversation where one party mentions a noun-item and the AI Mind needs to refer to the item as the one currently under discussion. We need to implement a rotation of the upstream variables from $us1 to $us7, so that any input noun will remain in the AI consciousness as something recently mentioned upstream in the conversation. We had better create a $usx variable for the InStantiate() module to transfer the concept number of an incoming noun to whichever $us1 to $us7 variable is up next in the rotation of up to seven recently mentioned noun-concepts.

We start testing the EnArticle() module to see if it is receiving a $usx transfer-variable from the InStantiate() module. At first it is not getting through. We change the conditions for calling EnArticle and a line of diagnostic code shows that $usx is getting through. Then we set up a conditional test for EnArticle() to say the word "the" if an incoming $usx matches the $us1 variable. We start seeing "THE" along with "A" in the output of our ghost.pl AI Mind, but there is not yet a rotation of the us1-us7 variables or a forgetting of any no-longer-recent concept.

We should create a rotating $usn number-variable to be a cyclic counter from one to seven and back to one again so that the upstream us1-us7 variables may rotate through their duty-function. We let $usn increment up to a value of seven over and over again. We pair up the $usn and us1-us7 variables to transfer the $usx value on a rotating basis. At first a problem arises when the ghost.pl AI says both "A" and "THE", but we insert a "return" statement so that EnArticle() will say only "A" and then skip the saying of "THE". We enter "you have a book" and a while later the AI outputs, "I HAVE THE BOOK."

pmpj0902

Using $t++ for discrete English and Russian MindBoot vocabulary.

In the ghost269.pl Perlmind it is time to switch portions of the MindBoot() sequence from hard-coded time-points to t-incremental time-points, as we have done already in the JavaScript AI and in the MindForth AI. We have saved the Perl AI for last because there are both English and Russian portions of the knowledge base (KB). We will put the hardcoded English KB first to be like the other AI Minds. Then we will put the hardcoded Russian KB followed by the t-incremental Russian vocabulary words so as to form a contiguous sequence. Finally we will put the t-incremental English vocabulary.

mfpj0901

Switching MindBoot from all hardcoded to partially t-increment coded.

Today in accordance with AI Go FOOM we need to start switching the MindBoot sequence from using only hardcoded time-points to using a harcoded knowledge-base followed by single-word vocabulary more loosely encoded with t-increment time-points. The non-hardcoded time-points will permit the Spawn module to make a copy of a running MindForth program after adding any recently learned concepts to the MindBoot sequence. It will also be easier for an AI Mind Maintainer to re-arrange the non-hardcoded sequence or to add new words to the sequence.

clpm0709

Extrapolating from the First Working AGI

Artificial General Intelligence (AGI) has arrived in MindForth and its JavaScript and Perl symbionts. Each Mind is expanding slowly from its core AGI functionality. The MindBoot sequence of innate concepts and ideas can be extended by the machine learning of new words or by the inclusion of more vocabulary in the MindBoot itself.

We may extrapolate from the current MindBoot by imagining a Perlmind that knows innately the entire Oxford English Dictionary (OED) and all of WordNet and all of Wikipedia. Such an AGI could be well on its way to artificial superintelligence.

If there is no upper bound on what a First Working AGI may know innately, why not make full use of Unicode and embed innately the vocabulary of all living human languages? Then go a step further and incorporate (incerebrate?) all the extinct languages of humanity, from LinearB to ancient Egyptian to a resurrected Proto-European. Add in Esperanto and Klingon and Lojban.

pmpj0706

Preventing unwarranted negation in the First Working AGI.

The First Working AGI (Artificial General Intelligence) has a problem in the ghost267.pl version written in Perl Five. After we trigger a logical inference by entering "anna is woman" and answering the question "DOES ANNA HAVE CHILD" with "no", the Perlmind properly adjusts the knowledge base (KB) and states the confirmed knowledge as "ANNA DOES NOT HAVE CHILD". Apparently the reentry of concept 502=ANNA back into the experiential memory is letting the InStantiate() module put too much activation on the 502=ANNA concept and the AI is erroneously outputting "ANNA BE NOT WOMAN". Since the original idea was "anna is woman", the real defect in the software is not so much the selection of the old idea but rather its unwarranted negation. When we change some code in the InStantiate() module to put a lower activation on reentrant concepts, the problem seemingly goes away, because the AI says "I HELP KIDS" instead of "ANNA BE NOT WOMAN", but as AI Mind Maintainers we need to track down where the unwarranted negation comes from.

The unwarranted negation comes from the OldConcept() module where the time-of-be-verb $tbev flag was being set for an 800=BE verb and was then accidentally carrying over its value as the improper place for inserting a 500=NOT $jux flag into an idea subsequently selected as a remembered thought. When we zero out $tbev at the end of OldConcept(), the Ghost AI stops negating the wrong memory.

pmpj0705

Improving the storage of conceptual flag-panels during input.

In the ghost266.pl Perlmind we need to improve upon a quick-and-dirty bugfix from our last coding session. After a silent inference and the operation of AskUser() calling EnAuxVerb(), the Ghost AI was going into the verb-concept of the inference-triggering input and replacing a correct $tkb value with a zero. Apparently the time-of-verb $tvb value, set in the Enparser() module during the parsing of a verb, was being erroneously carried over from the verb of user-input to the verb 830=DO in the EnAuxVerb() module during the generation of an inference-confirming question by the AskUser() module. Therefore the time-of-verb $tvb-flag needs to be reset to zero not during the generation of a response to user-input but rather at the end of the user-input. However, we find that we may not reset time-of-verb $tvb to zero during AudInput(), apparently because only character-recognition and not yet word-recognition has taken place. The $tvb-setting for a verb must remain valid throughout AudInput() so that the EnParser() module may use the time-of-verb $tvb flag to store a direct object as the $tkb of a verb. Accordingly we reset the $tvb-flag to zero in the Sensorium() module after the call to AudInput(). We stop seeing a $tkb of zero on the verb of an input that triggers automated reasoning with logical InFerence.

pmpj0703

Keeping AskUser from storing incorrect associative tags.

The ghost265.pl version of the Perlmind has a problem after making a logical inference. Instead of getting back to normal thinking, some glitch is causing the AI to say "ANNA BE NOT ANNA".

As we troubleshoot, we notice a problem with the initial, inference-evoking input of "anna is woman". The be-verb is being stored in the psy array with a $tkb of zero instead of the required time-point of where the concept of "WOMAN" is stored. This lack of a $nounlock causes problems later on, which do not warrant their own diagnosis because they are a result of the lacking $nounlock. We need to inspect the code for where the be-verb is being stored in the psy-array, but we are not sure whether the storage is occuring in the InStantiate() module, or in OldConcept(), or in EnParser(). We see that the Ghost AI is trying to store the be-verb in the EnParser() module with the correct tkb, but afterwards a tkb, of zero is showing up. We must check whether InStantiate() is changing what was stored in the EnParser() module.

Meanwhile we notice something strange. An input of "anna is person" gets stored properly with a correct $tkb, but "anna is woman" -- causing an inference -- is stored with a $tkb, of zero. When we enter "anna is robot", causing an inference and the output "DOES ANNA WANT BEEP", there is also a zero $tkb. Upshot: It turns out that the EnAuxVerb() module, called by AskUser() after an inference, was setting a wrong, carried-over value on the time-of-verb $tvb variable, which was then causing InStantiate() to go back to the wrong time-of-verb and set a zero value on the $tkb flag. So we zero out $tvb at the start of EnAuxVerb().

pmpj0701

Debugging the InFerence Function in the ghost.pl First Working AGI.

The ghost264.pl Perlmind has a minor bug which causes logical inference not to work if the inference is not triggered immediately at the start of running the program. If we let the AI run a little and then we type in "anna is woman", the AI answers "DOES ERROR HAVE CHILD" instead of "DOES ANNA HAVE CHILD". In the psy concept array of the silent inference, we observe that a zero is being recorded instead of the concept number "502" for Anna. The AI MindBoot is designed with the concept of "ERROR" placed at the beginning of the boot sequence so that any fruitless search for a concept will result automatically in an "ERROR" message if no concept is found. We suspect that some variable in the InFerence module is not being loaded with the correct value when the ghost.pl AI has already started thinking various thoughts.

The pertinent item in the InFerence() module is the $subjnom or "subject nominative" variable which is set outside of the module before InFerence is even called. We discover that the variable is spelled wrong in the OldConcept module, and we correct the spelling. It then seems that InFerence() can be called at any time and still operate properly. We decide to run the JavaScript AI to see if an inference has any problems if it is not the first order of business at the outset of an AI session. Nothing goes wrong, so the problem must have been the misspelling in the OldConcept() module.

During this coding session we also make a change in the KbRetro() module for the retroactive adjustment of the knowledge base (KB). We insert some code to put an arbitrary value of eight (8) on the $tru(th)-value variable for the noun at the start of the silent inference, such as "ANNA" in the silent inference "ANNA HAVE CHILD". When the human user either confirms or invalidates the inference, the resulting knowledge ought to have a positive truth-value, because someone has vouched for the truth or the negation of the inferred idea. We envision that the $tru(th)-value will serve the purpose of letting an AI Mind restrict its thinking to ideas which it believes and not to mere assertions or to ideas which were true yesterday but not today. We expect the $tru(th)-value to become fully operative in a robotic AI Mind for which "Seeing is believing" when visual recognition from cameras serving as eyes provides reliable knowledge to which a high $tru(th)-value may be assigned.

mfpj0624

Logical Inference in the First Working AGI MindForth

Over the past week fifteen or twenty hours of intense work went into coding the InFerence, AskUser and KbRetro modules in the Forth version of the First Working AGI. Interactively we could see that the Forthmind was making a silent inference from our input of "anna is a woman" but the AskUser module was substandardly asking "DO ANNA HAS CHILD?" in seeking confirmation of the silent inference. When we entered "no" as an answer, we could not see if the KbRetro module was properly inserting the 250=NOT adverb into the conceptual engrams of the silent inference so as to negate the inferred idea. Therefore today in the agi00056.F version of MindForth we are starting our diagnostic display about forty-five time-points earlier than the computed value of the time-of-input tin variable so that we can see if the inferred idea is being retroactively adjusted by KbRetro. At first blush, no insertion of 250=NOT is happening, so we start inserting diagnostic messages into the code.

Our diagnostics suggest that KbRetro is not being called, but why not? It turns out that we have not yet coded 404=NO or 432=YES or 230=MAYBE into the MindBoot sequence, so we code them in. Then we start getting a faulty output after answering "no" to AskUser. The AI says, "ANNA NOT NOT CHILD". Apparently EnVerbPhrase is not properly negating the refuted silent inference. After several hours of troubleshooting, the desired output appears.

When we enter "anna is woman" and we answer "no" to the question whether Anna has a child, the conceptual array shows the silent inference below at the time-points 3068-3070:

The arrays psy{ and ear{ show your input and the AI output:
time: tru psi hlc act mtx jux pos dba num mfn pre iob seq tkb rv -- pho act audpsi

3053 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3054 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3055 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3056 : 0 502 0 -40 0 0 5 1 1 2 0 0 800 3059 3053   65 0 502 A
3057 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3058 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   73 0 0 I
3059 : 0 800 0 -40 0 250 8 4 1 2 0 0 515 3065 3058   83 0 800 S
3060 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3061 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   87 0 0 W
3062 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   79 0 0 O
3063 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   77 0 0 M
3064 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3065 : 0 515 0 -40 0 0 5 0 2 2 0 0 0 0 3061   78 0 515 N
 066 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   13 0 0
3067 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3068 : 0 502 0 -26 0 0 5 1 1 0 0 0 810 3069 0   32 0 0
3069 : 0 810 0 56 0 250 8 0 0 0 502 0 525 3070 0   32 0 0
3070 : 0 525 0 32 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3071 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3072 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   68 0 0 D
3073 : 0 830 0 -40 0 0 8 0 1 2 0 0 810 0 3072   79 0 830 O
3074 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3075 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3076 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3077 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3078 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3079 : 0 502 0 -40 0 0 5 1 1 2 0 0 810 3084 3076   65 0 502 A
3080 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3081 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3082 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   72 0 0 H
3083 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3084 : 0 810 0 -40 0 0 8 4 2 2 0 0 525 3096 3082   83 0 810 S
3085 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3086 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3087 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   84 0 0 T
3088 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   72 0 0 H
3089 : 0 117 0 -40 0 0 1 0 1 2 0 0 810 0 3087   69 0 117 E
3090 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3091 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3092 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   67 0 0 C
3093 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   72 0 0 H
3094 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   73 0 0 I
3095 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   76 0 0 L
3096 : 0 525 0 -40 0 0 5 0 1 2 0 0 810 0 3092   68 0 525 D
3097 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3098 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3099 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3100 : 0 404 0 -40 0 0 4 0 1 2 0 0 0 0 3099   79 0 404 O
 101 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   13 0 0
3102 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3103 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3104 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3105 : 0 502 0 -42 0 0 5 1 1 2 0 0 810 3122 3102   65 0 502 A
3106 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3107 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3108 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   68 0 0 D
3109 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   79 0 0 O
3110 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   69 0 0 E
3111 : 0 830 0 -42 0 0 8 1 1 2 0 0 0 0 3108   83 0 830 S
3112 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3113 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3114 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   78 0 0 N
3115 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   79 0 0 O
3116 : 0 250 0 -42 0 0 2 1 1 2 0 0 0 0 3114   84 0 250 T
3117 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3118 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3119 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   72 0 0 H
3120 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   65 0 0 A
3121 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   86 0 0 V
3122 : 0 810 0 -42 0 250 8 4 2 2 0 0 525 3129 3119   69 0 810 E
3123 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3124 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3125 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   67 0 0 C
3126 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   72 0 0 H
3127 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   73 0 0 I
3128 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   76 0 0 L
3129 : 0 525 0 -42 0 0 5 1 1 2 0 0 0 0 3125   68 0 525 D
3130 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
3131 : 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0   32 0 0
time: tru psi hlc act mtx jux pos dba num mfn pre iob seq tkb rv

Robot alive since 2018-06-24:
ANNA  DOES  NOT  HAVE  CHILD

Since we negate the inference with our response of "no", KbRetro inserts the adverb "250" (NOT) at the time-point 3069 to negate the verb 810=HAVE. Then the AI states the activated idea of the negation of the inference: "ANNA DOES NOT HAVE CHILD".

mfpj0619

MindForth is the First Working AGI for robot embodiment.

The MindForth AGI needs updating with the new functionality coded into the JavaScript AI Mind, so today we start by adding two innate ideas to the MindBoot sequence. We add "ANNA SPEAKS RUSSIAN" so that the name "Anna" may be used for testing the InFerence mind-module by entering "anna is a woman". Then we add "I NEED A BODY" to encourage AI enthusiasts to work on the embodiment of MindForth in a robot. When we type in "anna is a woman", the AI responds "ANNA SPEAKS THE RUSSIAN", which means that InFerence is not ready in MindForth, and that the EnArticle module is too eager to insert the article "the", so we comment out a call to EnArticle for the time being. Then we proceed to implement the Indicative module as already implemented in the ghost.pl AGI and the JavaScript AI Mind. We also cause the EnVerbPhrase module to call SpreadAct for direct-object nouns, in case the AGI knows enough about the direct object to pursue a chain of thought.

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.