yes, I mean the primary archimedean field with “finite”. The fields go also “inside” in that 1/ω is in one that 1/ω2 is not in.
I mean the ambivalence point to be a mathematical statement rather than an empirical one about how expected value and infinites work. That is formulas of the form ω∗x=1 have a solution with x=1/ω and that w∗x<a,a=n∗r,n∈N,r∈R can be made true
The empirical part would involve a situation where the correct credence about it was truly infinidesimal. Currently we just designate the nearest real and call it a day. I have a suspicion that events that can happen but have probability 0 would benefit from going beyond real precision.
One can imagine dart competition. $20 for hitting the upper half of the board. $40 for hitting the upper and left half of the board. These two “challenges” or bets would be comparable in expected money if the dart lands uniformly on the board. How much money would be fair for landing squarely on the bullseye? For any small radius around the bullseye such a value is somewhat straighforward to get, yet any finite amount of money is not enough for the center itself. Yet presumably the center is not special and is as likely as any other. So if we are restricted to having a finite money payoff we can’t make an actually arbitrary target but must include infinitely many points to make up the target area. Even the vertical symmetry axis of the board is too narrow, a dart will almost surely that is to say with real probablity 1 land left or right on the board. It is not true that an infinite multiple of an infinidesimal needs to be finite. The vertical axis has more than finite multiples of points compared to the bullseye but it still fails to make a finite area for which a finite money payoff would be appropriate.
I don’t see how probablities for classes of futures neccesiates non-neglible real probabilities. Usually we want to be atleast real smooth but it is not clear to me that real smoothnes is good enough for all cases. This might be connected to the fact that if you integrate the probability density whether you are guaranteed to get a real or might you get something less than a real.
yes, I mean the primary archimedean field with “finite”. The fields go also “inside” in that 1/ω is in one that 1/ω2 is not in.
I mean the ambivalence point to be a mathematical statement rather than an empirical one about how expected value and infinites work. That is formulas of the form ω∗x=1 have a solution with x=1/ω and that w∗x<a,a=n∗r,n∈N,r∈R can be made true
The empirical part would involve a situation where the correct credence about it was truly infinidesimal. Currently we just designate the nearest real and call it a day. I have a suspicion that events that can happen but have probability 0 would benefit from going beyond real precision.
One can imagine dart competition. $20 for hitting the upper half of the board. $40 for hitting the upper and left half of the board. These two “challenges” or bets would be comparable in expected money if the dart lands uniformly on the board. How much money would be fair for landing squarely on the bullseye? For any small radius around the bullseye such a value is somewhat straighforward to get, yet any finite amount of money is not enough for the center itself. Yet presumably the center is not special and is as likely as any other. So if we are restricted to having a finite money payoff we can’t make an actually arbitrary target but must include infinitely many points to make up the target area. Even the vertical symmetry axis of the board is too narrow, a dart will almost surely that is to say with real probablity 1 land left or right on the board. It is not true that an infinite multiple of an infinidesimal needs to be finite. The vertical axis has more than finite multiples of points compared to the bullseye but it still fails to make a finite area for which a finite money payoff would be appropriate.
I don’t see how probablities for classes of futures neccesiates non-neglible real probabilities. Usually we want to be atleast real smooth but it is not clear to me that real smoothnes is good enough for all cases. This might be connected to the fact that if you integrate the probability density whether you are guaranteed to get a real or might you get something less than a real.