how do you find the sponsorships of studies and researchers?
I’d have to say the harder version is quite cool as well.
Yes, it’s a good point, that it’s a pattern that will pop up all over the place regardless. so the question is, if no one formally stated it (i.e identified it as a common pattern), how would it look? what scientific discoveries wouldn’t have been made? what wouldn’t have been invented? what would we have believed to be true that’s actually false? what bad decisions would we make? what good decision have we made because of it that we would have been able to make without it?
all examples would do, though the more impactful the better :)
Flowchart is gone :|
why not just delete his comments? (really asking)
Haven’t thought about that. it might. is there a way to test that? (i guess if you make it optional, as it is, then it won’t act that way)
Claim: this thread would be better (although, it’s already great) if people added confidence levels to their claims at the beginning, and updated them at the end of the discussion. (confidence level − 75%)
Related, street epistemology. it’s a practice similar to to Socratic questioning (“invented” by peter boghossian in his book ‘a manual for creating atheists’).
Here’s a live example (and two more channels. these also have lectures about it)
Thanks, it looks quite interesting, but unfortunately i don’t think i have the technical knowledge to understand most of the paper. can you make a quick summery of the relevant points?
But if we have to pick an age, it should be the SAME as other adult responsibilities
Here in Israel not even all voting is on the same age limit—elections for government are from 18, and municipal elections are from 17.
“Cortical white matter increases from childhood (~9 years) to adolescence (~14 years), most notably in the frontal and parietal cortices. Cortical grey matter development peaks at ~12 years of age in the frontal and parietal cortices, and 17 years in the temporal lobes (with the superior temporal cortex being last to mature) for women and they have reached full maturity at age 16-17. For men, they become fully mature at age 18. In terms of grey matter loss, the sensory and motor regions mature first, followed by other cortical regions. Human brain maturation continues to around 20 to 25 years of age.”
Pattern, i miscommunicated my question, i didn’t mean to ask about a Bayesian agent in the sense of a rational agent. just what is the mathematical result from plucking certain numbers into the equation.
I am well aware now and before the post, that a rational agent won’t have a 100% prior, and won’t find evidence equal to a 100%, that wasn’t where the question stemmed from.
correlation between improved-decision-making-skills, and moving from being 16 to 18 years old, seems somewhat weak and certainly not as strong as other predictors (education, self-reflection, IQ, etc.). also, it bears asking, why these certain ages—if 16 then why not 15? and if not 16, then why stay on 18 and not move to 19? cause AFAIK, the brain (frontal cortex) stops developing at age 24-25.
I grew up in a democratic school, my experience was that kids were far better at making decisions than the general population gave them credit for. and that it depended more on factors other than age.
anyone who says we should not lower the voting age for reasons of decreased decision making skills, should really ask himself why age based restrictions are OK, and other interventions that are sometimes suggested aren’t (like passing certain tests).
You can also fill it out more than once if you want.
I would add this sentence to the form description
This math is exactly why we say a rational agent can never assign a perfect 1 or 0 to any probability estimate.
Yes, of course. i just thought i found an amusing situation thinking about it.
You’re not confused about a given probability, you’re confused about how probability works.
nice way to put it :)
I think i might have framed the question wrong. it was clear to me that it wouldn’t be rational (so maybe i shouldn’t have used the term “Bayesian agent”). but it did seem that if you put the numbers this way you get a mathematical “definition” of “infinite confusion”.
I see. so -
If P(H) = 1.0 - ϵ1
And P(E|H) = 0 + ϵ2
Then it equals “infinite confusion”.
Am i correct?
and also, when you use epsilons, does it mean you get out of the “dogma” of 100%? or you still can’t update down from it?
And what i did in my post may just be another example of why you don’t put an actual 1.0 in your prior, cause then even if you get evidence of the same strength in the other direction, that would demand that you divide zero by zero. right?
Thanks for the answer! i was somewhat amused to see that it ends up being a zero divided by zero.
Does the ratio between 1epsilon over 2epsilon being undefined means that it’s arbitrarily close to half (since 1 over two is half, but that wouldn’t be exactly it)? or means that we get the same problem i specified in the question, where it could be anything from (almost) 0 to (almost) 1 and we have no idea what exactly?
I would add that the claim that “on average it’s good for such people to be punished” shouldn’t be thrown around unless there’s actually some quantification that suggests it. it may be a strong argument if it had some backing, but it isn’t any good if it doesn’t.
Can your system express sets that have multiple parent sets?
Yup, that was the idea. a strict hierarchy wouldn’t be an accurate map of the communities landscape. I think you would probably get some really weird nesting in some places (especially if we’re talking about individual users), but as long as it works and is intuitive to the user, it’s fine.
I am not sure i understand your middle sentence, but if i did then the system i proposed allows it. can you explain again?
books added since the list was last updated -
On applied Bayesian statistics, Dr_Manhattan recommends Lambert’s A student’s guide to Bayesian Statisticsover McEarlath’s Statistical Rethinking, Kruschke’s Doing Bayesian Data Analysis, and Gelman’s Bayesian Data Analysis.
On Functional Analysis, krnsll recommends Brezis’s Functional Analysis, Sobolev Spaces and Partial Differential Equationsover Kreyszig’s and Lax’s.
On Probability Theory, crab recommends Feller’s An Introduction to Probability Theory over Jaynes’ Probability Theory: The Logic of Science and MIT OpenCoursewar’s Introduction to Probability and Statistics.
On History of Economics, Pablo_Stafforini recommends Sandmo’s Economics Evolving over Robbins’ A History of Economic Thought and Schumpeter’s chaotic History of Economic Analysis.
On Relativity, PeterDonis recommends Carroll’s Spacetime and Geometry over Taylor & Wheeler’s Spacetime Physics, Misner, Thorne, & Wheeler’s Gravitation, Wald’s General Relativity, and Hawking & Ellis’s The Large Scale Structure of Spacetime.