1. Overview and Brain-Mind Diagram
/^^^^^^^^^\ enVocab Adds New English Vocabulary /^^^^^^^^^\
/ EYE \ / EAR \
/ \ CONCEPTS in SEMANTIC MEMORY / ________ \
| ______ | | | | _____ | / enBoot \ |
| / old \!!!!|!!!|!| | / \ | / English \ |
| / image \---|---|-+ | _____ / New- \ | \ "vault" / |
| \ recog / | |c| | / \ ( Concept ) | \________/ |
| \______/ | |a| | / Old- \ \_______/--|-------------\ |
| | |t| | ( Concept )--|---|----|----------\ | |
| visual | |s| | \_______/---|---|----|-------\ | | |
| | e| | | _|_______V_ | | c | | | |
| memory | a| | | / Parser \ | | a | | | |
| | t| | | \___________/ | | t | | | |
| reactivation | | |f| |noun? | | s-/ | | |
| | | |a| |verb? | | e | | |
| channel | | |u| ____V________ | | a | | |
| | | |n| ( Instantiate ) | | t-----/ | |
| ______ | | |a| \___________/ | | f | |
| / old \ | |_|_| / ________V_ | a | |
| / image \ | / \/ / \ | u | |
| \ store /---|--\ Psi / ( enVocab ) | n | |
| \______/ | \___/ \__________/ | a------/ |
diagrams.html shows a Theory of Mind.
The English vocabulary "enVocab" module stores the concept number
"nen" (number-English); initial activation "act" level zero; "fex"
(fiber-out) mindcore-exit tag; grammar part-of-speech "pos" tag;
"fin" (fiber-in) tag for concepts entering the Psi mindcore; and
"aud" tag for reactivating words in the auditory memory channel.
The software tags are the analog of associative tag fibers in the
CNS (central nervous system) mindgrid wetware of a human brain.
2. WORDS REMAIN IN THE AUDITORY CHANNEL
When the English enVocab module, the German deVocab module or any
other vocabulary module for a natural language creates new nodes
on the analog of lexical fibers in the semantic memory channel,
the actual phonemic words remain and move about in the auditory
memory channel, where the human or robot mind hears itself think.
The diagram ai4u_157.html is a flowchart of Mind.
// enExam() is a method of enNode()
// for access to English lexical nodes.
function enExam() { // ATM 18apr2002; ID & date.
en0 = this.nen;
en1 = this.act;
en2 = this.fex;
en3 = this.pos;
en4 = this.fin;
en5 = this.aud;
} // End of enExam method of enNode().
// enNode() is called from enVocab()
// to create or modify an English concept node:
function enNode(nen,act,fex,pos,fin,aud) { // ATM
this.nen = nen; // n(umber of) En(glish) concept;
this.act = act; // activation level;
this.fex = fex; // fiber-out (from Psi);
this.pos = pos; // grammatical part-of-speech;
this.fin = fin; // fiber-in (to Psi);
this.aud = aud; // aud(itory) recall-vector.
this.enExam = enExam; // a method of this object.
} // End of enNode(); return to enVocab().
// enVocab() is called from newConcept() or oldConcept()
// to create a node on a concept-fiber by "attaching"
// to it associative tags for En(glish) vocab(ulary).
// enVocab() suggests the possibility of coding
// frVocab() for French vocabulary (see ISO 639);
// deVocab() for (deutsch) German vocabulary; and
// jaVocab() for Japanese vocabulary, etc.
function enVocab() { // ATM 18apr2002; or your ID & date.
enLexicon[t] = new enNode(nen,0,fex,pos,fin,aud);
} // End of enVocab; return to oldConcept or newConcept.
\ enVocab is called from bootstrap; NEWCONCEPT or OLDCONCEPT
\ to create a node on a quasi-concept-fiber by "attaching"
\ to it associative tags for En(glish) vocab(ulary).
: enVocab \ ATM 21apr2002; or your ID & date.
( Number "nen" of English ) nen @ t @ 0 en{ !
( Do not store the activation level; it is a transient.)
( Store mindcore EXit tag. ) fex @ t @ 2 en{ !
( Store part of speech "pos".) pos @ t @ 3 en{ !
( Store mindcore IN tag. ) fin @ t @ 4 en{ !
( Store the auditory "aud" tag. ) aud @ t @ 5 en{ !
; \ End of enVocab; return to OLDCONCEPT or NEWCONCEPT.
5. ANALYSIS OF THE MODUS OPERANDI
enVocab gets values for each associative tag from other modules,
then inserts each value at the proper time-related point or node
on a ganged quasi-fiber in the En(glish) lexical memory array.
6. EXERCISES FOR STUDENTS OF ARTIFICIAL INTELLIGENCE
6.1. Code something like enVocab for a new AI or a new automaton.
Go from a stub, to fleshing out, to pushing the state of the art.
Try to design diagnostic and troubleshooting tools that will help
future generations of AI coders who take up where you leave off.
6.2. For users who have the option of installing your AI on their
Web site or in their robot just by copying and tweaking the code,
implement a start-up feature where they give the AI entity a name
that the childlike mind will adopt as its name for ever after.
If necessary, password-protect the self-concept name-word so that
only the human quasi-parent or the cyborg defining its identity
may change not the given name but the coded name of the cyborg.
For corporations operating a fleet or host or horde of robots,
consider using categorically valuable naming-patterns such as
Andru F-model Carnegiebot or Edsel O-Model Fordbot. Notice how
the addition of endings such as "-bot" or "-borg" may be used to
create a second-class company citizen of worker droids enlarging
the happy corporate "family" of not-yet-downsized human resources.
Armybot; Airbot or Flybot; Shipbot or Navybot are military names.
A robot makes an excellent officer and a supreme allied commander.
6.3. Implement the vocabulary module for a non-English language
and try to make the resulting AI bilingual or multilingual in the
set of natural languages where you have the necessary competence.
Be sure to include language-switching algorithms so that the Mind
may properly jump from language to language in both thinking and
speaking. Make an AI able to learn new languages. Then make an
AI able to create new human languages in the tradition of, say,
Esperanto. Finally let the AI community create its own language.
7. ENGLISH VOCABULARY AND ASSOCIATIVE-TAG RESOURCES
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