mfpj1005

MindForth resets associative tags before each operation of Indicative module.

In the MindForth artificial intelligence (AI) for robots, we will now start to display an apparatus of diagnostic messages at the start of the Indicative module to tell us the values being held in variables which serve the purpose of creating associative tags to interconnect the concepts being expressed as English words during the operation of the Indicative mind-module. Since the ConJoin module will often insert a conjunction between two thoughts being generated, the AI Mind Maintainer needs assurance that variable-values operative during one thought do not erroneously get carried over past a conjunction into the separate process of generating another thought.

Just by resetting the tsj time-of-subject variable to zero at the start of the Indicative module, we have made the Forthmind able to trigger repeated instances of logical InFerence. Each running of the Indicative module amounts to a fresh declaration of the associative tags in the conceptual flag-panel that supports the generation of ideas in the MindGrid. The following dialog still has a few problems, but it shows the repeated triggering of an inference.

john is a student
DOES  JOHN  READ  BOOKS  
no

  Indicative: tsj= 0 tvb= 0 tdo= 0
A  JOHN  DOES  NOT  READ  BOOKS
  Indicative: tsj= 0 tvb= 0 tdo= 0
PROFESSORS  TEACH  THE  STUDENTS  AND
  Indicative: tsj= 0 tvb= 0 tdo= 0
STUDENTS  READ  THE  BOOKS

  Indicative: tsj= 0 tvb= 0 tdo= 0
I  UNDERSTAND  YOU  AND
  Indicative: tsj= 0 tvb= 0 tdo= 0
YOU  ARE  A  MAGIC

andru is student
DOES  ANDRU  READ  THE  BOOKS  
no

  Indicative: tsj= 0 tvb= 0 tdo= 0
AN  ANDRU  DOES  NOT  READ  THE  BOOKS  AND
  Indicative: tsj= 0 tvb= 0 tdo= 0
YOU  READ  THE  BOOKS

  Indicative: tsj= 0 tvb= 0 tdo= 0
PROFESSORS  TEACH  THE  STUDENTS  AND
  Indicative: tsj= 0 tvb= 0 tdo= 0
STUDENTS  READ  THE  BOOKS

  Indicative: tsj= 0 tvb= 0 tdo= 0
STUDENTS  READ  THE  BOOKS  AND
  Indicative: tsj= 0 tvb= 0 tdo= 0
I  THINK

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.

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.

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.

may26mfpj

The MindForth Programming Journal (MFPJ) is both a tool in developing MindForth open-source artificial intelligence (AI) and an archival record of the history of how the AI Forthmind evolved over time.

1 Thurs.26.MAY.2011 -- Conditional Inhibition

In the recent Strong AI diaspora of MindForth and the tutorial AiMind.html program, we have implemented the neural inhibition of concepts immediately after they have been included in a generated thought. Now we would like to make inhibition occur when one or more responses must be made to a query involving nouns or a query involving verbs. The question "What do bears eat?" is a query of the what-do-X-verb variety involving one or more nouns as potentially valid answers as the direct object of the verb. If the noun of each single answer is immediately inhibited, the AI can respond with a different answer to a repeat of the question. Likewise, if we ask the AI, "What do robots do?", the query is of the what-do-X-do variety where potentially multiple verbs may need to be inhibited so as to give one valid answer after another, such as "Robots make tools" and "Robots sweep floors." If we are inhibiting the verbs, we do not want the direct-object nouns to be inhibited. We might need replies with different verbs but the same direct object, such as "Robots make tools" and "Robots use tools."

Inhibition may also play a role in calling the ConJoin module when a query elicits multiple thoughts which are the same sentence except for different nouns or different verbs. The responses, "Bears eat fish" and "Bears eat honey" could become "Bears eat fish and honey" if neural inhibition suppresses the repetition of subject and verb while calling the ConJoin module to insert the conjunction "AND" between the two answer nouns.

2 Thurs.26.MAY.2011 -- Problems With Determining Number

When we try to troubleshoot the Forthmind by entering "bears eat honey", a comedy of errors occurs. The AudRecog module contains a test to detect an "S" at the end of an English word and set the "num(ber)" value to two ("2") for plural. However, that test works only for recognized words, and not for a previously unknown word of new vocabulary. So the word "bears" gets tagged as singular by default, which causes the AI to issue erroneous output with "BEARS EATS HONEY", as if a singular subject is calling for "EATS" as a third person singular verb form.

The process of determining num(ber) ought to be more closely tied with the EnParser module, so that the parsing of a word as a noun should afford the AI a chance to declare plural number if the incoming noun ends with an "S".

Now we have inserted special code into the AudInput module to check for the input of nouns ending in "S", and to set the "num(ber)" variable to a plural value if a terminating "S" is found. For singular nouns like "bus" or "gas" that end in "S", we will have to devise techniques that override the default assumption of "S" meaning plural. We may use the article "A" or the verb "IS" as cues to declare a noun ending in "S" as singular.

Table of Contents

• 1 Thurs.26.MAY.2011 -- Conditional Inhibition

• 2 Thurs.26.MAY.2011 -- Problems With Determining Number