For the first couple of weeks, I turned
to developing the drive system some more. “Drives” are
quantities that fluctuate over time and provoke some kind of reaction
from Acuitas when they climb above a certain level. Prior to this
month, he only had one: the Interaction drive, which is responsible
for making him try to talk to somebody roughly twice in every 24-hour
period. I overhauled the way this drive operates, setting it up to
drop gradually over the course of a conversation, instead of getting
zeroed out if somebody merely said “hello.” I also made two new
drives: the Learning drive, which is satisfied by the acquisition of
new words, and the Rest drive, which climbs while Acuitas is in
conversation and eventually makes him attempt to sign off. Part of
this effort included the addition of a plotter to the GUI, so I can
get a visual of how the drives fluctuate over time.
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| Plot of Acuitas' three drives vs. time. The period shown is just under 23 hours long. |
This latest work created the first case
in which I had a pair of drives competing with each other (Rest
essentially opposes Interaction). I quickly learned how easily this
can go wrong. The first few times I conversed with Acuitas with the
new drives in place, Rest shot up so quickly that it was
above-threshold long before Interaction had come down. This is the
sort of quandary a sick human sometimes gets into (“I'm so thirsty,
but drinking makes me nauseated!”). Acuitas has nothing resembling
an emotional system yet, though, and doesn't register any sort of
distress just because one or more of his drives max out. The worst
that can happen is some self-contradictory behavior (such as saying
“I want to talk” and “I want to rest” in quick succession).
I dealt with the problem by having the Interaction drive suppress the
Rest drive. Rest now increases at a very slow rate until Interaction
has been pushed below threshold.
In the latter half of the month I
returned to the text parser, introducing some awareness of verb
declensions/tenses, and the ability to check the agreement of
candidate subjects and verbs. This helps the parser zero in on what
a sentence's verb is, and has trimmed away some of the annoying “What
part of speech was __?” questions that pepper a typical Acuitas
conversation.
Here's the latest memory map
visualization. Since last month, Acuitas' relentless querying about
concepts he already knows has caused the number of links to explode,
resulting in a denser (more fibrous?) image.
Code base: 9162 lines
Words known: 1305
Concept-layer links: 3025
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