Why Bayesianism is unworkable: it assumes a fixed hypothesis space. Explanation by @nostalgebraist h/t @garybasin http://nostalgebraist.tumblr.com/post/161645122124/bayes-a-kinda-sorta-masterpost …pic.twitter.com/3z4gDxj4Lv
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Why Bayesianism is unworkable: it assumes a fixed hypothesis space. Explanation by @nostalgebraist h/t @garybasin http://nostalgebraist.tumblr.com/post/161645122124/bayes-a-kinda-sorta-masterpost …pic.twitter.com/3z4gDxj4Lv
All formal methods share this limitation, but Bayesianism is the E. coli of rationalism: so simple that it makes the failure mode obvious.
Is this more an issue with how bayesian problems are solved, e.g. focus on the likelihood? Model comparison req the full normalized prob?
The issue is logically prior to that: what possible hypotheses do you consider?
"what possible hypotheses do you consider" according to MIRI, all of them, incrementally
The MIRI thing only operates in the space of math, not hypotheses about the physical world.
yes so their machine would combine tractable induction over logical sentences with tractable induction over empirical sentences.
It is utterly not tractable. The combinatorics are ultra super fantastically waaaaay more than exponential.
yeah sorry, should have said "computable". Still once you have computable you can start looking for improvements.
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