i like the identification of "salience" as a key factor, independent of probability distributions - i.e. if some options clearly stand out to you, you could reasonably assume that they would stand out to other people as well, and therefore be attractive parts of the total space of options. i.e. as a foreigner i would not have expected grand central terminal to be as salient as the empire state building, and indeed by the "probability distribution" framing i would not know whether to look at the choices as "there are several train stations and only one empire state building" or "there are several train stations and several notable skyscrapers, and now how rare are each category", but clearly grand central terminal has a cultural significance as a meeting point, which raises its salience independently of how many bits of information you need to pinpoint it.
i did expect the wikipedia article to talk about fixed points too, but maybe they are not as applicable a concept when considering a largely open set?
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i did expect the wikipedia article to talk about fixed points too, but maybe they are not as applicable a concept when considering a largely open set?