I take your point that the way an Infra-Bayesian system makes decisions isn’t the same as a human — it presumably doesn’t share our cognitive biases, and the pessimism element ‘Murphy’ in it seems stronger than for most humans. I normally assume that if there’s something I don’t understand about the environment that’s injecting noise into the outcome of my actions, the noise-related parts of results aren’t going to be well-optimized, so they’re going to be worse than I could have achieved had I had full understanding, but that even leaving things to chance I may sometimes get some good luck along with the bad — I don’t generally assume that everything I can’t control will have literally the worst possible outcome. So I guess in Infra-Bayesian terms I’m assuming that Murphy is somewhat constrained by laws that I’m not yet aware of, and may never be aware of.
My take on Murphy is that it’s a systematization of the force of entropy trying to revert the environment to a thermodynamic equilibrium state, and of the common fact that the utility of that equilibrium state is usually pretty low. One of the flaws I see in Infra-Bayesianism is that there are sometimes (hard to reach but physically possible) states whose utility to me is even lower than the thermodynamic equilibrium (such as a policy that scores less than 20% on a 5-option multiple choice quiz so does worse than random guessing, or a minefield left over after a war that is actually worse than a blasted wasteland) where increasing entropy would actually help improve things. In a hellworld, randomly throwing money wrenches in the gears is a moderately effective strategy. In those unusual cases Infra-Bayesianism’s Murphy no longer aligns with the actual effects of entropy/Knightian uncertainty.
I take your point that the way an Infra-Bayesian system makes decisions isn’t the same as a human — it presumably doesn’t share our cognitive biases, and the pessimism element ‘Murphy’ in it seems stronger than for most humans. I normally assume that if there’s something I don’t understand about the environment that’s injecting noise into the outcome of my actions, the noise-related parts of results aren’t going to be well-optimized, so they’re going to be worse than I could have achieved had I had full understanding, but that even leaving things to chance I may sometimes get some good luck along with the bad — I don’t generally assume that everything I can’t control will have literally the worst possible outcome. So I guess in Infra-Bayesian terms I’m assuming that Murphy is somewhat constrained by laws that I’m not yet aware of, and may never be aware of.
My take on Murphy is that it’s a systematization of the force of entropy trying to revert the environment to a thermodynamic equilibrium state, and of the common fact that the utility of that equilibrium state is usually pretty low. One of the flaws I see in Infra-Bayesianism is that there are sometimes (hard to reach but physically possible) states whose utility to me is even lower than the thermodynamic equilibrium (such as a policy that scores less than 20% on a 5-option multiple choice quiz so does worse than random guessing, or a minefield left over after a war that is actually worse than a blasted wasteland) where increasing entropy would actually help improve things. In a hellworld, randomly throwing money wrenches in the gears is a moderately effective strategy. In those unusual cases Infra-Bayesianism’s Murphy no longer aligns with the actual effects of entropy/Knightian uncertainty.