Esme Povirk @madewokherd@computerfairi.es

Ash has decided to coin the term "chronogenic" for headmates that are in some way a result of time travel.

@emerald Having a grounding trigger helped with that, I think, when we remembered to use it. (It was originally intended as a "break any active trances" trigger. Apparently a lot of things are secretly trances?)

@emerald Definitely interacted heavily with system stuff for me. Some system members seemed to have direct control while others had to yell at a golem and hope it listens.

Sorry, I'm not sure how coherent I am today.

Where I'm vaguely ending up is: motivations that are not healing or empowering are, though possibly temporarily effective, not sustainable. And motivations that are healing or empowering make us inconvenient.

I've been wondering since noticing this was a thing: how much of neurodivergent "executive dysfunction" is because the things that motivate neurotypical folks don't really work for us, and the things that work aren't taught to us? Followed by a vague swirling mass of: what might be the reasons/motivations behind that?

@emerald The way I would make myself do that specific thing would be: stop, rest, cultivate love. Specifically love for my present and future self would get me moving. Which also means that it doesn't make much difference whether it's me or someone else that will experience the eventual benefits, i.e. "gratification" on any timeline doesn't play into it.

(Being able to generate love in that way took a lot of work though.)

@emerald I feel like even if the reward were immediate, it wouldn't actually influence my behavior.

@mavica_again Maybe we're designed to create dumb shit so no one can call us productive?

@viridian Yeah, that's one of the reasons we tend to do intra-system hypnosis instead.

Playing my own randomizer https://www.twitch.tv/madewokherd/

@viridian Is this approach still going to work when I start randomizing land unlock requirements (which means I have to calculate reachability)?

The naive algorithm is not as slow as I expected, in this case. I suspect that in other cases we'll have a problem.

So, I still have no good solution. I guess we go naive for now.

Turns out I do not understand this as well as I thought. PlaceOrbsInLands in this example (even though that's not quite how I actually wrote it) has a probability of failure that's proportional to the ideal failure probability, for one step, but it's lower than that ideal. For it to be the same, we'd have to stop everything immediately after encountering any failure. But, if it is the same, we end up with an equivalent of trying every permutation.

And now I have to rewrite my placement algorithm because I realized while writing this that I took some shortcuts that may not be valid.

This is actually easy. The probability of stopping based on this specific orb that we placed should be 1/N * (probability of a valid combination based on having placed that orb). Well, the probability of PlaceOrbsInLands failing is equal to the second term in that multiplication, so we can treat this the same as an invalid pairing. It doesn't really matter that there might be some valid ones.

OK, so what if an orb placement succeeds? We still have to place the rest of them. For that, we call PlaceOrbsInLands for our remaining set of lands and orbs. If it succeeds, great. We add the one pair placed in this step, and return the list.

If it fails, we need to decide whether to stop at this step. We want to do that in such a way that the overall probability of returning failure is proportional to the number of valid permutations given our input state.

If we move on to trying a second orb after a failure, and that one also fails, we should return failure a total of 2/N of the time. But we already did the 1/N check, so at this stage we should return failure 1/(N-1) of the time, to increase the total probability to where we need it.