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Thought: I think Pascal's Mugging can't harm boundedly rational agents. If an agent is bounded in its computing power, then what it ought to do is draw some bounded number of samples from its mixture model of possible worlds, and then evaluate the expected value of its actions in the sample rather than across the entire mixture. As the available computing power approaches infinity, the sample size approaches infinity, and the sample more closely resembles the true distribution, thus causing the expected utility calculation to approach the true expected utility across the infinite ensemble of possible worlds. But, as long as we employ a finite sample, the more-probable worlds are so overwhelmingly more likely to be sampled that the boundedly rational agent will never waste its finite computing power on Pascal's Muggings: it will spend more computing power examining the possibility that it has spontaneously come into existence as a consequence of an Infinite Improbability Drive being ignited in its near vicinity than on true Muggings.
There are other ways of taking Pascal's mugging into account. You shouldn't do that based on lack of computing power. And if you aren't doing it based on lack of computing power, why involve randomness at all? Why not work out what an agent would probably do after N samples, or something like that?