Is there a principled reason to use the MMEU strategy is the face of Knightian uncertainty? Why not maximize maximum expected utility, or minimized expected regret (i.e. the difference between the expected utility obtained by your action and the best expected utility you could have achieved if you knew the results of the Knightian uncertainty ahead of time).
Also, if we have two different types of uncertainty, is there a good reason that there shouldn’t be more than that? Maybe,
) Here’s a thing that I can confidently assign a probability to (e.g. the outcome of a coin flip)
) Here’s a thing that I cannot usually assign a precise probability to, but that it should be possible in principle to make such an assignment (e.g. the number of yellow balls in the bin)
*) Here’s a thing that that I would have trouble even in principle assigning a meaningful probability to (e.g. the simulation hypothesis)
Is there a principled reason to use the MMEU strategy is the face of Knightian uncertainty? Why not maximize maximum expected utility, or minimized expected regret (i.e. the difference between the expected utility obtained by your action and the best expected utility you could have achieved if you knew the results of the Knightian uncertainty ahead of time).
Also, if we have two different types of uncertainty, is there a good reason that there shouldn’t be more than that? Maybe, ) Here’s a thing that I can confidently assign a probability to (e.g. the outcome of a coin flip) ) Here’s a thing that I cannot usually assign a precise probability to, but that it should be possible in principle to make such an assignment (e.g. the number of yellow balls in the bin) *) Here’s a thing that that I would have trouble even in principle assigning a meaningful probability to (e.g. the simulation hypothesis)