On a prediction market platform, consider the graph of accounts and money flows between them. Some metrics take the form of adding up how much money flows across a boundary, subtracting backwards flows: How much currency is ever minted and paid out to users; how much currency is ever removed from circulation via fees. But for measuring how well the platform funnels money into smarter hands, it’s not clear how to draw a boundary around “the smart accounts”. Do you agree that analogous generalizations of Markov blankets should be applicable for both problems?
I don’t think that requires a generalization of Markov blankets, I think plain old Markov blankets should just work. The fact that it’s not clear how to draw the boundary corresponds to the difficulty of figuring out which blanket to use; the answer should be a Markov blanket.
Point-estimated Drake equation parameters cause the Fermi paradox, point-estimated utility functions cause paperclips and I don’t expect a point-estimated Markov blanket to go well here either.
On a prediction market platform, consider the graph of accounts and money flows between them. Some metrics take the form of adding up how much money flows across a boundary, subtracting backwards flows: How much currency is ever minted and paid out to users; how much currency is ever removed from circulation via fees. But for measuring how well the platform funnels money into smarter hands, it’s not clear how to draw a boundary around “the smart accounts”. Do you agree that analogous generalizations of Markov blankets should be applicable for both problems?
I don’t think that requires a generalization of Markov blankets, I think plain old Markov blankets should just work. The fact that it’s not clear how to draw the boundary corresponds to the difficulty of figuring out which blanket to use; the answer should be a Markov blanket.
Point-estimated Drake equation parameters cause the Fermi paradox, point-estimated utility functions cause paperclips and I don’t expect a point-estimated Markov blanket to go well here either.