Cyborg AI Minds programmed to think in memory of the hundreds of murdered Chinese Tiananmen June 4th demonstrators are a true concept-based artificial intelligence with natural language understanding, simple at first and lacking robot embodiment, and expandable all the way to human-level intelligence and beyond. Privacy policy: Third parties advertising here may place and read cookies on your browser; and may use web beacons to collect information as a result of ads displayed here.

Saturday, October 05, 2019

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

Friday, October 04, 2019

mfpj1004

Using parameters to declare the time-points of conceptual instantiation.

[2019-10-02] Recently we have expanded the conceptual flag-panel of MindForth from fifteen tags to twenty-one associative tags, so that the free open-source artificial intelligence for robots may think a much wider variety of thoughts in English. Then we had to debug the function of the InFerence module to restore its ability to reason from two known facts in order to infer a new fact. For instance, the Forthmind knows the fact that students read books, and we tell the AI the fact that John is a student. Then the AI infers that perhaps John, being a student, reads books, and the incredibly brilliant Forth software asks us, "Does John read books?" We may answer yes, no, maybe or no response at all. Currently, though, we have the problem that InFerence works only once and fails to deal properly with repeated attempts to trigger an inference. We suspect that some of the variables involved in the process of automated reasoning are not being reset properly to their status ex quo ante before we made the first test of InFerence. Therefore we shall try a new technique of debugging which we have developed recently in one of the other AI Minds, namely the ghost.pl AI that thinks in both English and in Russian. We create a diagnostic display at the start of the EnThink module for thinking in English, so that we may see the values held by the variables associated with the InFerence module and the KbRetro module that retroactively adjusts the knowledge base (KB) of the AI Mind in accordance with whatever answer we have given when the AskUser module asks us to validate or contradict an inference. The following dialog shows us that some variables are not being properly reset to zero.

john is student

EnThink: becon= 1 yncon= 0 ynverb= 0 inft= 0
qusub= 0 qusnum= 1 subjnom= 504 prednom= 561 tkbn= 0
quverb= 0 seqverb= 0 seqtkb= 0 tkbv= 0
quobj= 0 dobseq= 0 kbzap= 0 tkbo= 0
DOES JOHN READ BOOKS
no

EnThink: becon= 0 yncon= 0 ynverb= 0 inft= 2084
qusub= 504 qusnum= 1 subjnom= 0 prednom= 0 tkbn= 2086
quverb= 863 seqverb= 0 seqtkb= 0 tkbv= 2087
quobj= 540 dobseq= 0 kbzap= 404 tkbo= 2088
A JOHN DOES NOT READ BOOKS

EnThink: becon= 0 yncon= 0 ynverb= 0 inft= 2118
qusub= 504 qusnum= 1 subjnom= 0 prednom= 0 tkbn= 0
quverb= 863 seqverb= 0 seqtkb= 0 tkbv= 0
quobj= 0 dobseq= 0 kbzap= 0 tkbo= 2088
PROFESSORS TEACH THE STUDENTS AND STUDENTS READ THE BOOKS

EnThink: becon= 0 yncon= 0 ynverb= 0 inft= 2152
qusub= 504 qusnum= 1 subjnom= 0 prednom= 0 tkbn= 0
quverb= 863 seqverb= 0 seqtkb= 0 tkbv= 0
quobj= 0 dobseq= 0 kbzap= 0 tkbo= 2088
I UNDERSTAND YOU AND YOU ARE A MAGIC
andru is student

EnThink: becon= 1 yncon= 0 ynverb= 0 inft= 2220
qusub= 504 qusnum= 1 subjnom= 501 prednom= 561 tkbn= 0
quverb= 863 seqverb= 0 seqtkb= 0 tkbv= 0
quobj= 0 dobseq= 0 kbzap= 0 tkbo= 2088
DOES ANDRU READ THE STUDENTS
Because some of the variables have not been reset, a second attempt to trigger an inference with "andru is student" results in a faulty query that should have been "Does Andru read books?" Let us reset the necessary variables and try again.

Upshot: It still does not work, because of a more difficult and more obscure bug in the assignment of conceptual associative tags. Well, back to the salt mines.

https://groups.google.com/d/msg/comp.lang.forth/xN3LRYEd5rw/uuUroGzhBAAJ

[2019-10-04] We may have made a minor breakthrough in the InStantiate module by doing one instantiation and by then using parameters such as part of speech (pos) and case (dba) to declare the initial time-points for subjects, verbs and objects. The EnParser module may then retroactively alter or modify the associative tags embedded at each identified time-point.