Suppose b is the true bias of the coin (which the supercomputer will compute). Then your expected return in this game is
š¯”¼[max(b, 0.50)] = 0.50 + š¯”¼[max(b-0.50, 0)]
No. That formula would imply that, if the coin is 30% for sure and you buy it for 0.3, you make 0.2 in expectation, which you donā€™t, you make 0 regardless of what price you buy at.
Note that this kind of problem has also shown up in decision theory more generally. This is a good place to start. In particular, it seems like your problem can be fixed with epsilon exploration (if it doesnā€™t do so automatically, as per Soares), both the EDT and CDT variant should work.
No. That formula would imply that, if the coin is 30% for sure and you buy it for 0.3, you make 0.2 in expectation, which you donā€™t, you make 0 regardless of what price you buy at.
Note that this kind of problem has also shown up in decision theory more generally. This is a good place to start. In particular, it seems like your problem can be fixed with epsilon exploration (if it doesnā€™t do so automatically, as per Soares), both the EDT and CDT variant should work.