BLUF: I have another argument in favor of choosing courses of action via recently produced, quantum-generated random numbers.
Recently, I wrote a long post about a decision criterion for choosing Courses of Action (CoA) under moral uncertainty given the Many-Worlds Interpretation of quantum mechanics. While this has been shot down on LessWrong and I am still working on formalizing my intuition regarding relative choice-worthiness (a combination of Bayesian moral uncertainty and traditional expected utility), as well as figuring out exactly what it means to live in a Many-Worlds universe, I tentatively believe I have another argument in favor of entropy-driven CoA selection: computational intractability.
Traditional decision theory has not focused a ton, to my knowledge, on the process of agents actually computing real world expected-utility estimates. I think the simplest models basically assume agents have infinite computations available. What decision is an agent to make when they are far from being done computing the expected-utility of different CoA? Of course, this depends on the algorithm they use, but in general, what decision should they make when the time to make a decision comes early?
In a Many-Worlds universe, I am inclined to think agents should deliberately throw entropy into their decisions. If they have explored the optimization space to the point where they are 60% sure they have found the optimal decision, they should literally seek out a quantum mechanics generated random number–in this case between 1 and 5–and if the number is 1, 2, or 3, they should choose the course of action they are confident in; otherwise, they should choose a different promising course of action. This ensures that child worlds are appropriately diversifying so “all of our eggs are not in one basket”.
If the fundamental processes in the universe–from statistical mechanics to the strong economic forces present today in local worlds based on human evolutionary psychology–lean in favor of well-being over suffering, then I argue that this diversification is anti-fragile.
A loose analogy (there are slightly different principles at play) is investing in a financial portfolio. If you really don’t know which stock is going to take off, you probably don’t want to throw all your money into one stock. And choosing courses of action based on quantum random number generation is *the only* way to reasonably diversify one’s portfolio; even if one feels very uncertain about one’s decision, in the majority of child worlds, one will have made that very same decision. The high-level processes of the human brain are generally robust against any single truly random quantum mechanics event.
I am still working on understanding what the generic distribution of child worlds looks like under Many-Worlds, so I am far from completely certain that this decision-making principle is ideal. However, because it does seem promising, I am seeking to obtain a hardware true random number generator to experiment with this principle–I won’t learn the actual outcomes, which have to be predicted from first-principles, but I can learn how it feels psychologically to implement this protocol. At this point, it looks like I am going to have to make one. I’ll add to this post when I do.