This is really silly, but I found myself wondering today, while I was watching my creatures caught in these infinite loops of expressing their love and adoration for each other, exactly how chatty educated vs non-educated creatures are. And I mean like, scientifically. I know that creatures who know their vocabulary end up talking to each other more, but I wanted numbers. I wanted to know, specifically, what circumstances produced the most speech Bubbles Per Creature Per Minute.
So I threw together a script. It sticks a constructor script into the speech bubbles which runs whenever they are created to keep a tally of the number of speech bubbles being generated in the world, then outputs to the debug monitor every time 1000 speech bubbles have been counted, or each time the population changes.
setv game "amk_labs_speech_bubble_total" 0
setv game "amk_labs_speech_bubble_start_tick" wtik
setv game "amk_labs_speech_bubble_start_norns" totl 4 0 0
*runs every time a speech bubble is created, effectively
*counting the number of speech bubbles ever created in the world
*to measure how 'chatty' creautres are.
*note this will also count speech bubbles created by the hand or agents!
scrp 1 2 9 10
inst
addv game "amk_labs_speech_bubble_total" 1
doif game "amk_labs_speech_bubble_total" ge 1000 or totl 4 0 0 ne game "amk_labs_speech_bubble_start_norns"
doif game "amk_labs_speech_bubble_start_norns" > 0
setv va00 wtik
subv va00 game "amk_labs_speech_bubble_start_tick"
divv va00 20.0
divv va00 60.0
sets va01 "Took "
adds va01 vtos va00
adds va01 " minutes to reach "
adds va01 vtos game "amk_labs_speech_bubble_total"
adds va01 " speech bubbles with "
adds va01 vtos game "amk_labs_speech_bubble_start_norns"
adds va01 " creatures (average "
setv va02 itof game "amk_labs_speech_bubble_total"
divv va02 game "amk_labs_speech_bubble_start_norns"
divv va02 va00
adds va01 vtos va02
adds va01 " bpcpm)"
dbg: outs va01
else
dbg: outs "There aren't any norns!"
endi
setv game "amk_labs_speech_bubble_total" 0
setv game "amk_labs_speech_bubble_start_tick" wtik
setv game "amk_labs_speech_bubble_start_norns" totl 4 0 0
endi
endm
rscr
scrx 1 2 9 10
setv game "amk_labs_speech_bubble_total" 0
setv game "amk_labs_speech_bubble_start_tick" 0
setv game "amk_labs_speech_bubble_start_norns" 0
For the first round I used a script that maintained the population at 10 TWB adult male chichis (so they wouldn’t breed), auto-vocabed, and let it run for a few hours. The results varied a little but were mostly were fairly consistent, averaging between 5 and 7 speech bubbles per creature per minute.
Took 16.125000 minutes to reach 1000 speech bubbles with 10 creatures (average 6.201550 bpcpm)
Took 15.870833 minutes to reach 1000 speech bubbles with 10 creatures (average 6.300866 bpcpm)
Took 17.002501 minutes to reach 1000 speech bubbles with 10 creatures (average 5.881488 bpcpm)
Took 18.480001 minutes to reach 1000 speech bubbles with 10 creatures (average 5.411255 bpcpm)
Took 16.979166 minutes to reach 1000 speech bubbles with 10 creatures (average 5.889571 bpcpm)
Took 18.455833 minutes to reach 1000 speech bubbles with 10 creatures (average 5.418341 bpcpm)
Took 15.663333 minutes to reach 1000 speech bubbles with 10 creatures (average 6.384337 bpcpm)
Took 14.100000 minutes to reach 1000 speech bubbles with 10 creatures (average 7.092198 bpcpm)
Took 20.185833 minutes to reach 1000 speech bubbles with 10 creatures (average 4.953969 bpcpm)
Took 16.850000 minutes to reach 1000 speech bubbles with 10 creatures (average 5.934718 bpcpm)
Took 19.864166 minutes to reach 1000 speech bubbles with 10 creatures (average 5.034191 bpcpm)
Took 19.315001 minutes to reach 1000 speech bubbles with 10 creatures (average 5.177323 bpcpm)
Took 17.909168 minutes to reach 1000 speech bubbles with 10 creatures (average 5.583732 bpcpm)
Took 16.351665 minutes to reach 1000 speech bubbles with 10 creatures (average 6.115585 bpcpm)
Took 17.385000 minutes to reach 1000 speech bubbles with 10 creatures (average 5.752085 bpcpm)
Took 17.319166 minutes to reach 1000 speech bubbles with 10 creatures (average 5.773950 bpcpm)
Then I tried the same thing, but without auto-vocabing them, and with the HLM disabled. Unsurprisingly, these creatures were significantly less chatty without getting caught in all those express and forf loops that only pop up when creatures understand each other, with the average BPCPM just under 3.
Took 35.280003 minutes to reach 1000 speech bubbles with 10 creatures (average 2.834467 bpcpm)
Took 33.806667 minutes to reach 1000 speech bubbles with 10 creatures (average 2.957996 bpcpm)
Took 34.297501 minutes to reach 1000 speech bubbles with 10 creatures (average 2.915664 bpcpm)
Took 30.084999 minutes to reach 1000 speech bubbles with 10 creatures (average 3.323916 bpcpm)
Took 35.925835 minutes to reach 1000 speech bubbles with 10 creatures (average 2.783512 bpcpm)
Took 35.858334 minutes to reach 1000 speech bubbles with 10 creatures (average 2.788752 bpcpm)
Took 35.183334 minutes to reach 1000 speech bubbles with 10 creatures (average 2.842255 bpcpm)
Just to confirm though, I repeated the experiment in a few different configurations:
With 20 adult vocb’d norns, the BPCPM was even higher, up to 13! I guess that makes sense, with more creatures there were surely even more conversations going on that every creature absolutely had to weigh in on.
Took 7.664167 minutes to reach 1000 speech bubbles with 20 creatures (average 6.523866 bpcpm)
Took 4.015833 minutes to reach 1000 speech bubbles with 20 creatures (average 12.450716 bpcpm)
Took 3.757500 minutes to reach 1000 speech bubbles with 20 creatures (average 13.306720 bpcpm)
Took 4.419167 minutes to reach 1000 speech bubbles with 20 creatures (average 11.314351 bpcpm)
Took 4.069167 minutes to reach 1000 speech bubbles with 20 creatures (average 12.287528 bpcpm)
Took 4.143333 minutes to reach 1000 speech bubbles with 20 creatures (average 12.067578 bpcpm)
Took 6.448333 minutes to reach 1000 speech bubbles with 20 creatures (average 7.753942 bpcpm)
Took 5.773333 minutes to reach 1000 speech bubbles with 20 creatures (average 8.660508 bpcpm)
Took 5.640000 minutes to reach 1000 speech bubbles with 20 creatures (average 8.865249 bpcpm)
Took 5.216667 minutes to reach 1000 speech bubbles with 20 creatures (average 9.584664 bpcpm)
Took 4.288333 minutes to reach 1000 speech bubbles with 20 creatures (average 11.659542 bpcpm)
Took 4.890000 minutes to reach 1000 speech bubbles with 20 creatures (average 10.224949 bpcpm)
Took 5.535000 minutes to reach 1000 speech bubbles with 20 creatures (average 9.033423 bpcpm)
Meanwhile, with 20 adult not-vocb’d norns, the BPCPM was about the same as with 10 norns. Makes sense, considering more creatures who can’t understand each other aren’t going to converse much.
Took 17.689167 minutes to reach 1000 speech bubbles with 20 creatures (average 2.826589 bpcpm)
Took 19.781668 minutes to reach 1000 speech bubbles with 20 creatures (average 2.527593 bpcpm)
Took 17.166666 minutes to reach 1000 speech bubbles with 20 creatures (average 2.912621 bpcpm)
Took 19.006666 minutes to reach 1000 speech bubbles with 20 creatures (average 2.630656 bpcpm)
Took 19.464167 minutes to reach 1000 speech bubbles with 20 creatures (average 2.568823 bpcpm)
Took 15.960834 minutes to reach 1000 speech bubbles with 20 creatures (average 3.132668 bpcpm)
Took 16.730000 minutes to reach 1000 speech bubbles with 20 creatures (average 2.988643 bpcpm)
With a single adult vocb’d norn, unsurprisingly significantly lower. Knowledge doesn’t really help you with no one to talk to.
Took 319.990021 minutes to reach 1000 speech bubbles with 1 creatures (average 3.125098 bpcpm)
Took 343.740814 minutes to reach 1000 speech bubbles with 1 creatures (average 2.909169 bpcpm)
Took 337.059174 minutes to reach 1000 speech bubbles with 1 creatures (average 2.966838 bpcpm)
With a single adult not-vocb’d norn, the results were about the same. So it really is nearly entirely the interactions with other creatures that results in increased bibbling, as I guessed.
It is a little interesting that the not-vocab’d norn did seem to chatter ever so slightly less than the vocab’d norn, even when alone. It’s such a small margin that it might very well just be a coincidence, but if there is an actual difference, I wonder what causes it?
Took 338.799164 minutes to reach 1000 speech bubbles with 1 creatures (average 2.951601 bpcpm)
Took 351.045837 minutes to reach 1000 speech bubbles with 1 creatures (average 2.848631 bpcpm)
Took 348.990021 minutes to reach 1000 speech bubbles with 1 creatures (average 2.865412 bpcpm)
Took 348.859985 minutes to reach 1000 speech bubbles with 1 creatures (average 2.866479 bpcpm)
With two adult vocb’d norns, it was a little higher, of course. But it wasn’t near as much as with 10 or 20 creatures involved. It was also a little erratic-- probably due to them occasionally wandering apart from each other for periods of alone time.
Took 116.809166 minutes to reach 1000 speech bubbles with 2 creatures (average 4.280486 bpcpm)
Took 139.866669 minutes to reach 1000 speech bubbles with 2 creatures (average 3.574833 bpcpm)
Took 119.535835 minutes to reach 1000 speech bubbles with 2 creatures (average 4.182846 bpcpm)
Took 144.057510 minutes to reach 1000 speech bubbles with 2 creatures (average 3.470836 bpcpm)
Took 161.455002 minutes to reach 1000 speech bubbles with 2 creatures (average 3.096838 bpcpm)
With two adult not-vocb’d norns, for the sake of control. Results were consistent with all other not-vocab’d norns, though again, just slightly higher in an amount that could very well be coincidence.
Took 166.394180 minutes to reach 1000 speech bubbles with 2 creatures (average 3.004913 bpcpm)
Took 171.785843 minutes to reach 1000 speech bubbles with 2 creatures (average 2.910601 bpcpm)
Took 160.511673 minutes to reach 1000 speech bubbles with 2 creatures (average 3.115038 bpcpm)
Took 157.593323 minutes to reach 1000 speech bubbles with 2 creatures (average 3.172723 bpcpm)
Just to see if age was a factor at all, I tried again with 10 baby (or at least, not auto-aged to adult) vocb’d norns. The results were more or less the same as the adult run.
Took 15.401667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.492804 bpcpm)
Took 13.973333 minutes to reach 1000 speech bubbles with 10 creatures (average 7.156488 bpcpm)
Took 17.902500 minutes to reach 1000 speech bubbles with 10 creatures (average 5.585812 bpcpm)
Took 15.961667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.265010 bpcpm)
Took 16.762501 minutes to reach 1000 speech bubbles with 10 creatures (average 5.965697 bpcpm)
Took 19.042501 minutes to reach 1000 speech bubbles with 10 creatures (average 5.251411 bpcpm)
Took 17.073334 minutes to reach 1000 speech bubbles with 10 creatures (average 5.857087 bpcpm)
Took 20.209999 minutes to reach 1000 speech bubbles with 10 creatures (average 4.948046 bpcpm)
Took 17.518333 minutes to reach 1000 speech bubbles with 10 creatures (average 5.708305 bpcpm)
Took 18.066668 minutes to reach 1000 speech bubbles with 10 creatures (average 5.535055 bpcpm)
With 10 baby not-vocb’d norns as a control, with the expected results.
Took 41.227497 minutes to reach 1000 speech bubbles with 10 creatures (average 2.425566 bpcpm)
Took 36.710003 minutes to reach 1000 speech bubbles with 10 creatures (average 2.724053 bpcpm)
Took 33.963333 minutes to reach 1000 speech bubbles with 10 creatures (average 2.944352 bpcpm)
Took 36.605835 minutes to reach 1000 speech bubbles with 10 creatures (average 2.731805 bpcpm)
Took 35.958332 minutes to reach 1000 speech bubbles with 10 creatures (average 2.780997 bpcpm)
Took 33.415833 minutes to reach 1000 speech bubbles with 10 creatures (average 2.992593 bpcpm)
Took 37.156666 minutes to reach 1000 speech bubbles with 10 creatures (average 2.691307 bpcpm)
Took 36.654167 minutes to reach 1000 speech bubbles with 10 creatures (average 2.728203 bpcpm)
Took 35.195000 minutes to reach 1000 speech bubbles with 10 creatures (average 2.841313 bpcpm)
Took 33.961666 minutes to reach 1000 speech bubbles with 10 creatures (average 2.944496 bpcpm)
I can’t imagine results will be any different with female norns but I wouldn’t be a very good scientist if I didn’t do a run with them too, just to rule out any potential differences. I was a little surprised that they seemed to actually turn up with a slightly higher BPCPM. It’s one of those so-small-it-might-just-be-random things, but it’s a little more significant than previous differences, so… hm. Maybe at a later point I’ll test it more intensively.
Took 14.279166 minutes to reach 1000 speech bubbles with 10 creatures (average 7.003210 bpcpm)
Took 13.149167 minutes to reach 1000 speech bubbles with 10 creatures (average 7.605044 bpcpm)
Took 12.033334 minutes to reach 1000 speech bubbles with 10 creatures (average 8.310249 bpcpm)
Took 12.375834 minutes to reach 1000 speech bubbles with 10 creatures (average 8.080264 bpcpm)
Took 16.011667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.245446 bpcpm)
Took 18.106667 minutes to reach 1000 speech bubbles with 10 creatures (average 5.522828 bpcpm)
Took 17.701666 minutes to reach 1000 speech bubbles with 10 creatures (average 5.649186 bpcpm)
Took 16.171667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.183654 bpcpm)
Took 16.437500 minutes to reach 1000 speech bubbles with 10 creatures (average 6.083650 bpcpm)
Took 17.730833 minutes to reach 1000 speech bubbles with 10 creatures (average 5.639893 bpcpm)
Took 17.153332 minutes to reach 1000 speech bubbles with 10 creatures (average 5.829771 bpcpm)
10 not-vocab’d female norns, on the other hand, came out pretty much on par with others for untaught creatures.
Took 41.900833 minutes to reach 1000 speech bubbles with 10 creatures (average 2.386587 bpcpm)
Took 40.848331 minutes to reach 1000 speech bubbles with 10 creatures (average 2.448080 bpcpm)
Took 36.109169 minutes to reach 1000 speech bubbles with 10 creatures (average 2.769380 bpcpm)
Took 33.936665 minutes to reach 1000 speech bubbles with 10 creatures (average 2.946666 bpcpm)
Took 33.746666 minutes to reach 1000 speech bubbles with 10 creatures (average 2.963256 bpcpm)
Took 35.007500 minutes to reach 1000 speech bubbles with 10 creatures (average 2.856531 bpcpm)
Took 33.930000 minutes to reach 1000 speech bubbles with 10 creatures (average 2.947244 bpcpm)
Took 34.463333 minutes to reach 1000 speech bubbles with 10 creatures (average 2.901635 bpcpm)
I could have run even more experiments with grendels and ettins and non-TWBs and NB creatures, but I really feel like at this point I’ve mostly just been beating the lifeless equine of what we already knew, which is that well-educated creatures will use a lot of breath talking to each other. So now to get more to the actual point of what I wanted to do here.
I wrote a weird little agent, a sort of invisible, traveling learning machine that enums around to every creature in the world and teaches it a random word. I’ve been thinking about something like this for a while as a way for creatures to learn speech more slowly and gradually even if the player doesn’t take the time to teach them. In a final version, this agent will only show up for a quick tutor session when the creature is off camera, to avoid breaking immersion, and will only show up very occasionally, paced with the aim of getting an unattended creature a nearly full vocabulary just before adulthood.
But for the sake of this experiment, I had a different goal in mind. I wanted to see selectively not teaching words that they use to communicate with each other would reduce overall chatter.
This was a little more difficult to science out precisely because I couldn’t keep the tutor agent running alongside the speech bubble counter-- that would send the count out of control. And leaving my usual population maintenance script running would do me no good, since that only produces fully-trained or totally untrained norns, and that would throw things off. I ended up rewriting my population maintenance script to rely on imported creatures instead of creating new ones, pre-trained a bunch of creatures with the new agent, and then exported them.
For the first run of 10 norns, the only word I omitted from their vocabulary was “maybe.” This wasn’t going to stop them from getting into love/like/dislike loops, but I thought it might cut down on the “maybe eat elevator”-type bibblings as a whole. However, it seemed this was not the case. It seems not knowing the word “maybe” isn’t the thing that keeps them from responding.
But when I think about it, that makes sense. Making a suggestion to another creature doesn’t in any way depend on that creature understanding you. What matters really is that you understand the creature expressing the need. The only way to stop a creature from making a suggestion in response to a need being expressed would be to eliminate all the drive words so the creatures couldn’t express their needs at all, and well, at that point you almost may as well not teach them any words at all.
The extremely bizarre thing, however, is that the BPCPM for these creatures was absolutely off the charts, and I had no idea why. It’s so absurd, in fact, that I double-checked my code and re-ran the experiment with normal creatures again to make sure nothing had gone awry. But when I tried the maybe-less creatures again I still got the same, off the wall results, with numbers of 20 to 25 BPCPM, roughly four times the chattering of perfectly educated norns!
Took 4.720000 minutes to reach 1000 speech bubbles with 10 creatures (average 21.186440 bpcpm)
Took 4.793334 minutes to reach 1000 speech bubbles with 10 creatures (average 20.862309 bpcpm)
Took 4.364167 minutes to reach 1000 speech bubbles with 10 creatures (average 22.913881 bpcpm)
Took 4.496666 minutes to reach 1000 speech bubbles with 10 creatures (average 22.238697 bpcpm)
Took 4.216667 minutes to reach 1000 speech bubbles with 10 creatures (average 23.715414 bpcpm)
Took 3.880833 minutes to reach 1000 speech bubbles with 10 creatures (average 25.767662 bpcpm)
Took 4.015833 minutes to reach 1000 speech bubbles with 10 creatures (average 24.901432 bpcpm)
Took 3.867500 minutes to reach 1000 speech bubbles with 10 creatures (average 25.856497 bpcpm)
Took 3.903333 minutes to reach 1000 speech bubbles with 10 creatures (average 25.619129 bpcpm)
Took 4.140833 minutes to reach 1000 speech bubbles with 10 creatures (average 24.149729 bpcpm)
Took 3.755000 minutes to reach 1000 speech bubbles with 10 creatures (average 26.631157 bpcpm)
Took 3.597500 minutes to reach 1000 speech bubbles with 10 creatures (average 27.797081 bpcpm)
Took 3.495833 minutes to reach 1000 speech bubbles with 10 creatures (average 28.605482 bpcpm)
Took 3.937500 minutes to reach 1000 speech bubbles with 10 creatures (average 25.396826 bpcpm)
Took 3.952500 minutes to reach 1000 speech bubbles with 10 creatures (average 25.300444 bpcpm)
Took 3.728333 minutes to reach 1000 speech bubbles with 10 creatures (average 26.821636 bpcpm)
Took 4.000834 minutes to reach 1000 speech bubbles with 10 creatures (average 24.994791 bpcpm)
Took 3.964167 minutes to reach 1000 speech bubbles with 10 creatures (average 25.225981 bpcpm)
When I took the game out of fast ticks to watch, I could see why. These creatures absolutely could not stop talking about how much they loved each other. It was constant and unrelenting and easily explained the high numbers. But why these creatures? How could the simple elimination of the word maybe from their vocabulary have such an effect?!
What actually happens when a creature suggests something to another creature? Does it prompt them to think about doing it? Does their inability to understand each other’s suggestions result in fewer interruptions to their train of thought? Is never making suggestions to another living being the secret to world peace??
I repeated the experiment with an entirely new batch of creatures. And while the results were eventually similar, I noticed it took a little time to ramp up to maximum chattiness. That makes some amount of sense, considering it takes a little time for creatures to get to know and love each other on the levels that they do.
There’s still other factors that I needed to rule out before attributing all this love the lack of a “maybe.” It was possible that the exporting/importing process was affecting things somehow. I also wondered if the teaching agent had something to do with priming their minds for the tight bond they shared. If I recalled correctly, creatures come to like and dislike each other based on the experiences that the have in the vicinity of those creatures, not necessarily how those specific creatures have treated them. So it’s possible that all that learning-spam was seen as a positive experience to them, and that teaching them together in huge batches was creating some positive shared memories.
But as I ran the experiment for longer, I watched the BPC take a dip when a creature or two died and was replaced by a freshly imported norn before returning back their super high loving levels. This implies to me that the love involved is learned after the teaching process, but it’s not impossible that the group learning is still having an impact.
Took 16.510834 minutes to reach 1000 speech bubbles with 10 creatures (average 6.056629 bpcpm)
Took 21.242500 minutes to reach 1000 speech bubbles with 10 creatures (average 4.707544 bpcpm)
Took 8.943333 minutes to reach 1000 speech bubbles with 10 creatures (average 11.181514 bpcpm)
Took 4.862500 minutes to reach 1000 speech bubbles with 10 creatures (average 20.565552 bpcpm)
Took 5.094167 minutes to reach 1000 speech bubbles with 10 creatures (average 19.630295 bpcpm)
Took 4.932500 minutes to reach 1000 speech bubbles with 10 creatures (average 20.273693 bpcpm)
Took 4.634166 minutes to reach 1000 speech bubbles with 10 creatures (average 21.578856 bpcpm)
Took 4.233333 minutes to reach 1000 speech bubbles with 10 creatures (average 23.622049 bpcpm)
Took 3.763333 minutes to reach 1000 speech bubbles with 10 creatures (average 26.572187 bpcpm)
Took 3.479167 minutes to reach 1000 speech bubbles with 10 creatures (average 28.742514 bpcpm)
Took 3.475833 minutes to reach 1000 speech bubbles with 10 creatures (average 28.770079 bpcpm)
Took 3.455000 minutes to reach 1000 speech bubbles with 10 creatures (average 28.943560 bpcpm)
Took 3.540000 minutes to reach 1000 speech bubbles with 10 creatures (average 28.248589 bpcpm)
I wasn’t sure what to test first, but my curiosity was most pressing on the group learning aspect. So I slowly created one creature at a time, running the tutor agent on each one until they seemed to grasp everything (except ‘maybe’, of course), and then exported them. It only took a few minutes per creature, but it was substantially slower than teaching them in batches of 10 like I was previously. I started hashing through some ideas to refine my tutor agent to make it “smarter” by detecting if a creature already knew a word so it wouldn’t re-teach it, and for the agent to be able to tell when a creature’s vocabulary is complete and set a flag as such. That might be an appropriate goal for a final, release-ready version of the agent, but I didn’t feel like putting in that much effort just yet.
The results of the individually tested norns was… interesting. They did in fact eventually ramp up to the absurd high BPC (and amount of love!) but it did take them a lot longer to get there. This suggests to me that there’s a combination of factors involved. Spending their childhoods together certainly primes them for greater affection, but it doesn’t seem to have anything to do with their capacity to reach these high levels of affection.
This is also making me question the results of my other studies, because I don’t think I actually let them run this long. I realize I’m getting a little out of scope here, but I feel like I have to be certain that this increased affection over time doesn’t happen in a longer-run scenario. So I repeated the original experiment a couple times, letting vocb’d norns run around for a lot longer. And over time, watching several sets of creatures grow old together it seemed, the BPC did seem to creep upward, ever so slightly But it wasn’t anywhere near the near the 20-25 of the agent-tutored groups. It was more like they started out at around 5-7 BPC and leveled off at closer to 6-8 BPC, getting up to 10 once or twice.
I considered that if I was going to get really precise results, I was going to have to start controlling a lot of factors and gathering more specific data. For example, I could start tracking every word said by every creature and start tracking the actual words spoken, and additionally track each time the population control script had to replace a creature to more directly see the impact of introducing the new creatures to the group. I could track every individual creature’s BPC and gather other details like their age to see what the impact was there. But that was a ton of work, and I wasn’t ready to go there just yet.
Took 25.005001 minutes to reach 1000 speech bubbles with 10 creatures (average 3.999200 bpcpm)
Took 15.373334 minutes to reach 1000 speech bubbles with 10 creatures (average 6.504770 bpcpm)
Took 18.446667 minutes to reach 1000 speech bubbles with 10 creatures (average 5.421033 bpcpm)
Took 18.523335 minutes to reach 1000 speech bubbles with 10 creatures (average 5.398596 bpcpm)
Took 7.268333 minutes to reach 1000 speech bubbles with 10 creatures (average 13.758312 bpcpm)
Took 6.414167 minutes to reach 1000 speech bubbles with 10 creatures (average 15.590489 bpcpm)
Took 6.060000 minutes to reach 1000 speech bubbles with 10 creatures (average 16.501650 bpcpm)
Took 5.310833 minutes to reach 1000 speech bubbles with 10 creatures (average 18.829435 bpcpm)
Took 5.600000 minutes to reach 1000 speech bubbles with 10 creatures (average 17.857143 bpcpm)
Took 4.807500 minutes to reach 1000 speech bubbles with 10 creatures (average 20.800831 bpcpm)
Took 3.914167 minutes to reach 1000 speech bubbles with 10 creatures (average 25.548222 bpcpm)
Took 3.519166 minutes to reach 1000 speech bubbles with 10 creatures (average 28.415819 bpcpm)
Took 3.551667 minutes to reach 1000 speech bubbles with 10 creatures (average 28.155794 bpcpm)
Took 3.733333 minutes to reach 1000 speech bubbles with 10 creatures (average 26.785715 bpcpm)
Took 4.054167 minutes to reach 1000 speech bubbles with 10 creatures (average 24.665981 bpcpm)
Took 3.698333 minutes to reach 1000 speech bubbles with 10 creatures (average 27.039207 bpcpm)
Took 4.107500 minutes to reach 1000 speech bubbles with 10 creatures (average 24.345709 bpcpm)
Took 3.692500 minutes to reach 1000 speech bubbles with 10 creatures (average 27.081923 bpcpm)
Took 3.799167 minutes to reach 1000 speech bubbles with 10 creatures (average 26.321562 bpcpm)
Took 3.603333 minutes to reach 1000 speech bubbles with 10 creatures (average 27.752083 bpcpm)
Took 3.610833 minutes to reach 1000 speech bubbles with 10 creatures (average 27.694439 bpcpm)
Took 3.491667 minutes to reach 1000 speech bubbles with 10 creatures (average 28.639620 bpcpm)
Took 3.560000 minutes to reach 1000 speech bubbles with 10 creatures (average 28.089886 bpcpm)
Took 3.505833 minutes to reach 1000 speech bubbles with 10 creatures (average 28.523888 bpcpm)
Took 3.455000 minutes to reach 1000 speech bubbles with 10 creatures (average 28.943560 bpcpm)
First, I wanted to investigate more of my methods for interference. So I removed the “maybe” exclusion from my agent-tutor. In theory, this meant that the creatures taught with the agent would be every bit as educated as the vocb’d creatures in the original trial. If the results proved similar, then we might be able to assume that it was, in fact, the removal of the word “maybe” that was responsible for this spike of affection, and not the number of other factors that changed. But I doubted this was the case.
And yeah, sure enough, the norns eventually turned to endless loving chatter and ramped up their numbers. But it did happen more slowly than it did in other group-tested trials. So it might still be something of a factor? But it’s definitely not the defining factor.
Took 10.044168 minutes to reach 1000 speech bubbles with 10 creatures (average 9.956027 bpcpm)
Took 13.076666 minutes to reach 1000 speech bubbles with 10 creatures (average 7.647209 bpcpm)
Took 10.466666 minutes to reach 1000 speech bubbles with 10 creatures (average 9.554140 bpcpm)
Took 15.531667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.438459 bpcpm)
Took 12.901667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.750937 bpcpm)
Took 8.778334 minutes to reach 1000 speech bubbles with 10 creatures (average 11.391684 bpcpm)
Took 6.514167 minutes to reach 1000 speech bubbles with 10 creatures (average 15.351157 bpcpm)
Took 5.304167 minutes to reach 1000 speech bubbles with 10 creatures (average 18.853102 bpcpm)
Took 5.421667 minutes to reach 1000 speech bubbles with 10 creatures (average 18.444513 bpcpm)
Took 5.200000 minutes to reach 1000 speech bubbles with 10 creatures (average 19.230770 bpcpm)
Took 4.150000 minutes to reach 1000 speech bubbles with 10 creatures (average 24.096384 bpcpm)
Took 4.043334 minutes to reach 1000 speech bubbles with 10 creatures (average 24.732067 bpcpm)
Took 3.960833 minutes to reach 1000 speech bubbles with 10 creatures (average 25.247213 bpcpm)
Took 3.740000 minutes to reach 1000 speech bubbles with 10 creatures (average 26.737968 bpcpm)
So what is it about the tutor-agent that makes creatures so affectionate towards each other? Do creatures for some reason interpret all that agent-learning as… socialization? I feel like I would have to delve even deeper into creature brains to figure out what is going on here, and I’m tired.
I’ve also gotten a little off track here. I didn’t expect to be troubleshooting weird side effects of my agent.
Okay, let’s try something else, again, just to rule it out, I thought. Let’s make batches of vocb’d norns, let them run around a few minutes, and then export them. Then re-import them using the same population manager script that I used for the agent-tutor norns, and then start measuring their chattiness. If the results are similar to those of creatures in the runs that were created instead of imported, it should completely narrow down the agent-tutor as the only difference between the groups, and therefore the cause of the excess love-chatter.
And yes, as it turns out, the results are closer to that of the original experiment. A little higher, oddly, but again, nothing like the agent-tutored norns. It seems the tutor-agent is to blame, as much as one can “blame” the agent of, apparently, eternal love and world peace.
Took 13.679999 minutes to reach 1000 speech bubbles with 10 creatures (average 7.309942 bpcpm)
Took 10.715000 minutes to reach 1000 speech bubbles with 10 creatures (average 9.332711 bpcpm)
Took 13.111667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.626795 bpcpm)
Took 11.755833 minutes to reach 1000 speech bubbles with 10 creatures (average 8.506415 bpcpm)
Took 13.196667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.577671 bpcpm)
Took 15.044168 minutes to reach 1000 speech bubbles with 10 creatures (average 6.647094 bpcpm)
Took 13.990001 minutes to reach 1000 speech bubbles with 10 creatures (average 7.147963 bpcpm)
Took 14.223333 minutes to reach 1000 speech bubbles with 10 creatures (average 7.030701 bpcpm)
Took 11.944167 minutes to reach 1000 speech bubbles with 10 creatures (average 8.372288 bpcpm)
Just to sate my curiosity, I did a set of three runs (one untrained, one vocb’d, and one agent-tutored) on stock chichis, instead of the TWBs I’ve been using. My thought process was that if the tendency to love-chatter excessively when agent-tutored is not present in stock chichis, that will narrow down my “why” analysis to the differences between stock chichis and TWBs rather than the genomes as a whole.
And wow, yes, interestingly the agent-tutored stock chichis are not more chattery than the vocb’d chichis. Their BPC is pretty much the same, and even after letting them run through a few lifetimes, they’re not as affectionate as the TWB sets. So whatever love-priming effect the tutor agent has seems exclusive to TWBs.
Took 13.530833 minutes to reach 1000 speech bubbles with 10 creatures (average 7.390528 bpcpm)
Took 12.816667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.802341 bpcpm)
Took 15.670000 minutes to reach 1000 speech bubbles with 10 creatures (average 6.381621 bpcpm)
Took 13.792500 minutes to reach 1000 speech bubbles with 10 creatures (average 7.250318 bpcpm)
Took 18.766666 minutes to reach 1000 speech bubbles with 10 creatures (average 5.328597 bpcpm)
Took 16.266666 minutes to reach 1000 speech bubbles with 10 creatures (average 6.147541 bpcpm)
Took 17.115000 minutes to reach 1000 speech bubbles with 10 creatures (average 5.842828 bpcpm)
Took 14.058333 minutes to reach 1000 speech bubbles with 10 creatures (average 7.113219 bpcpm)
Took 14.941667 minutes to reach 1000 speech bubbles with 10 creatures (average 6.692694 bpcpm)
I don’t have access to the genetics kit on my linux PC and the interface of liveGMS is too cumbersome for me to comb through to find reasons for this. At some point I do need to do a full analysis of the TWB genome for my own understanding, but I’ve already far derailed myself from the original purpose of this experiment.
Getting back to what I wanted to do all along, I modified my agent tutor to avoid teaching creatures the words Love, Like, Dislike, and Hate. The results were creatures that chattered at a rate that was similar to vocb’d norns, in that 6-8 BPC range, much quieter.
Even though they couldn’t understand each other’s expressions of love (and therefore didn’t get into loops chattering about it), these creatures were still incredibly affectionate, gathering in piles, kissing and tickling each other.
Took 13.946667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.170172 bpcpm)
Took 16.938334 minutes to reach 1000 speech bubbles with 10 creatures (average 5.903769 bpcpm)
Took 17.878332 minutes to reach 1000 speech bubbles with 10 creatures (average 5.593363 bpcpm)
Took 14.106668 minutes to reach 1000 speech bubbles with 10 creatures (average 7.088847 bpcpm)
Took 15.198334 minutes to reach 1000 speech bubbles with 10 creatures (average 6.579669 bpcpm)
Took 15.418333 minutes to reach 1000 speech bubbles with 10 creatures (average 6.485785 bpcpm)
Took 17.894999 minutes to reach 1000 speech bubbles with 10 creatures (average 5.588153 bpcpm)
Took 14.260834 minutes to reach 1000 speech bubbles with 10 creatures (average 7.012213 bpcpm)
Took 16.885000 minutes to reach 1000 speech bubbles with 10 creatures (average 5.922416 bpcpm)
Took 13.812500 minutes to reach 1000 speech bubbles with 10 creatures (average 7.239819 bpcpm)
Took 16.375000 minutes to reach 1000 speech bubbles with 10 creatures (average 6.106870 bpcpm)
Took 15.218333 minutes to reach 1000 speech bubbles with 10 creatures (average 6.571022 bpcpm)
Took 14.740001 minutes to reach 1000 speech bubbles with 10 creatures (average 6.784260 bpcpm)
Took 14.327500 minutes to reach 1000 speech bubbles with 10 creatures (average 6.979585 bpcpm)
Took 12.160000 minutes to reach 1000 speech bubbles with 10 creatures (average 8.223684 bpcpm)
While it was nice to see creatures fondly grooming each other without being exceptionally loud about it, it was a bit of a shame that I couldn’t understand what they were saying. I wondered if maybe if I partially taught them the words, maybe I could understand them without them being able to understand each other. So, just once, I used Magic Words Hand-Teaching to teach them the word for Love, which they learned as “lolo.”
This backfired tremendously.
I guess if a creature even has the slightest idea of what a word
is, they will understand
other creatures using it. Almost immediately the entire group
started gushing about how much they “lolo” each other,
and the BPC skyrocketed to 25 in a matter of minutes. Oh dear.
I love these affectionate creatures. And I do appreciate that I can use this tutor-agent to opt out of teaching them the words to express that and overall keep them from getting stuck in those loud gossip loops, even at the price of not being able to understand them myself.
But I’m worried that this tutor-agent has artificially inflated their affection, and I don’t necessarily always want that.
So I guess it’s time for me to rewrite the tutor agent in a smarter form that teaches creatures words slowly over the course of their childhood, only as they need them, and see if that has a different effect than spamming them with hundreds of speech bubbles at the moment they are born. That’s what I ultimately need this agent to do anyway, so I may as well get it into the form I intend on using it in before testing further.
I was about to finally wrap this set of experiments up and go work on refining the tutor agent, when I had this One Last Idea.
I generated 10 untrained norns and, using Magic Words Hand Teaching, taught them the word “love” and only the word “love.” I didn’t use the tutor agent. I simply spammed “teach love” about a dozen times, and let them run. They didn’t know any other words. I also left the population maintenance script running, which generated a new norn each time one died, but didn’t teach any of the new norns the word.
The results were fascinating. While it started out slowly, it seemed that once they ramped up, they were also very affectionate and couldn’t stop talking about it. But I hadn’t taught them with the tutor agent. They didn’t get spammed with tons of learning right out of the shell-- only maybe a dozen or so lines.
Their BPC wasn’t quite as high as the agent-tutored norns, but at least some of that was probably because without the ability to express their needs, other creatures couldn’t respond to them, so I was essentially missing all the “maybe” lines. It was still nearly double the rate of vocb’d creatures.
Took 41.101669 minutes to reach 1000 speech bubbles with 10 creatures (average 2.432991 bpcpm)
Took 27.240833 minutes to reach 1000 speech bubbles with 10 creatures (average 3.670960 bpcpm)
Took 8.410000 minutes to reach 1000 speech bubbles with 10 creatures (average 11.890607 bpcpm)
Took 6.890000 minutes to reach 1000 speech bubbles with 10 creatures (average 14.513788 bpcpm)
Took 7.776667 minutes to reach 1000 speech bubbles with 10 creatures (average 12.858980 bpcpm)
Took 4.857500 minutes to reach 1000 speech bubbles with 10 creatures (average 20.586721 bpcpm)
Took 5.624167 minutes to reach 1000 speech bubbles with 10 creatures (average 17.780411 bpcpm)
Took 5.122500 minutes to reach 1000 speech bubbles with 10 creatures (average 19.521719 bpcpm)
Took 5.569167 minutes to reach 1000 speech bubbles with 10 creatures (average 17.956007 bpcpm)
Took 5.594167 minutes to reach 1000 speech bubbles with 10 creatures (average 17.875763 bpcpm)
Took 5.699167 minutes to reach 1000 speech bubbles with 10 creatures (average 17.546425 bpcpm)
Took 5.857500 minutes to reach 1000 speech bubbles with 10 creatures (average 17.072130 bpcpm)
Took 6.374167 minutes to reach 1000 speech bubbles with 10 creatures (average 15.688325 bpcpm)
Took 5.533333 minutes to reach 1000 speech bubbles with 10 creatures (average 18.072289 bpcpm)
Took 5.365000 minutes to reach 1000 speech bubbles with 10 creatures (average 18.639330 bpcpm)
Took 5.285000 minutes to reach 1000 speech bubbles with 10 creatures (average 18.921474 bpcpm)
Took 5.711667 minutes to reach 1000 speech bubbles with 10 creatures (average 17.508024 bpcpm)
Took 5.772500 minutes to reach 1000 speech bubbles with 10 creatures (average 17.323517 bpcpm)
Took 5.940834 minutes to reach 1000 speech bubbles with 10 creatures (average 16.832655 bpcpm)
Took 6.686667 minutes to reach 1000 speech bubbles with 10 creatures (average 14.955134 bpcpm)
Took 6.442500 minutes to reach 1000 speech bubbles with 10 creatures (average 15.521926 bpcpm)
Took 6.739167 minutes to reach 1000 speech bubbles with 10 creatures (average 14.838630 bpcpm)
As the norns who were taught ‘love’ lived out their lifespans and were replaced with creatures who didn’t know the word, the BPC went down to the levels of the completely untrained norns. The tribe didn’t pass on their language, but they did pass on their affection. Still the creatures huddled in a pile near the emphatic vendor, smooching like there’s no tomorrow.
Maybe I should make another script to count the number of times creatures push each other, rather than just watching them. That would be the more scientific way to measure what was going on here.
The fact that creatures who were not taught the word ‘love’ were just as affectionate as the ones that were taught the word ‘love’ leads me to believe that the actual teaching is what is making them affectionate, regardless of the words used.
I have veered way off track here-- initially I just wanted to see if I could avoid excess gossip chatter by leaving out certain words, and I guess I determined that I can. But now I’m just really curious why the difference between TWBs of ‘average’ affection levels and hyper-affectionate TWBs seems to be a handful of URGE SHOU’s.
Took 7.662500 minutes to reach 1000 speech bubbles with 10 creatures (average 13.050571 bpcpm)
Took 8.021667 minutes to reach 1000 speech bubbles with 10 creatures (average 12.466237 bpcpm)
Took 7.935000 minutes to reach 1000 speech bubbles with 10 creatures (average 12.602394 bpcpm)
Took 7.616667 minutes to reach 1000 speech bubbles with 10 creatures (average 13.129103 bpcpm)
Took 13.556667 minutes to reach 1000 speech bubbles with 10 creatures (average 7.376444 bpcpm)
Took 13.604167 minutes to reach 1000 speech bubbles with 10 creatures (average 7.350689 bpcpm)
Took 23.750000 minutes to reach 1000 speech bubbles with 10 creatures (average 4.210526 bpcpm)
Took 34.672501 minutes to reach 1000 speech bubbles with 10 creatures (average 2.884130 bpcpm)
Took 36.667500 minutes to reach 1000 speech bubbles with 10 creatures (average 2.727211 bpcpm)
Took 34.958332 minutes to reach 1000 speech bubbles with 10 creatures (average 2.860548 bpcpm)
Took 34.096668 minutes to reach 1000 speech bubbles with 10 creatures (average 2.932838 bpcpm)
Took 34.280003 minutes to reach 1000 speech bubbles with 10 creatures (average 2.917153 bpcpm)
Took 33.119167 minutes to reach 1000 speech bubbles with 10 creatures (average 3.019400 bpcpm)
Took 36.316666 minutes to reach 1000 speech bubbles with 10 creatures (average 2.753557 bpcpm)
I keep telling myself I’m too tired and I really should work on something else, but unfortunately my brain has decided we’re going to obsess over this highly specific question, so I did, in fact, mod the kiss and tickle scripts to add counters to them. More tests will have to happen later, though, or I will be up all night again.