Utility functions are families of mappings from futures to reals, which don’t live in an affine space, as you mention.
Are you sure? The only thing one really wants from a utility function is ranking, which is even weaker a requirement than affine spaces. All monotonic remappings are in the same equivalency class.
The only thing one really wants from a utility function is ranking, which is even weaker a requirement than affine spaces.
It’s practically useful to have reals rather than rankings, because that lets one determine how the function will behave for different probabilistic combinations of futures. If you already have the function fully specified over uncertain futures, then only providing a ranking is sufficient for the output.
The reason why I mentioned that it was a mapping, though, is because the output of a single utility function can be seen as an affine space. The point I was making in the ancestral posts was that while it looks like the outputs of two different utility functions play nicely, careful consideration shows that their combination destroys the mapping, which is what makes utility functions useful.
All monotonic remappings are in the same equivalency class.
I’m hearing an echo of praxeology here; specifically the notion that humans use something like stack-ranking rather than comparison of real-valued utilities to make decisions. This seems like it could be investigated neurologically ….
Huh, no. If army1987.U($1000) = shminux.U($1000) = 1, army1987.U($10,000) = 1.9, shminux.U($10,000) = 2.1, and army1987.U($100,000) = shminux.U($100,000) = 3, then then I would prefer 50% probability of $1000 and 50% probability of $100,000 rather than 100% probability of $10,000, and you wouldn’t.
Are you sure? The only thing one really wants from a utility function is ranking, which is even weaker a requirement than affine spaces. All monotonic remappings are in the same equivalency class.
It’s practically useful to have reals rather than rankings, because that lets one determine how the function will behave for different probabilistic combinations of futures. If you already have the function fully specified over uncertain futures, then only providing a ranking is sufficient for the output.
The reason why I mentioned that it was a mapping, though, is because the output of a single utility function can be seen as an affine space. The point I was making in the ancestral posts was that while it looks like the outputs of two different utility functions play nicely, careful consideration shows that their combination destroys the mapping, which is what makes utility functions useful.
Hence the ‘families’ comment.
I’m hearing an echo of praxeology here; specifically the notion that humans use something like stack-ranking rather than comparison of real-valued utilities to make decisions. This seems like it could be investigated neurologically ….
Huh, no. If army1987.U($1000) = shminux.U($1000) = 1, army1987.U($10,000) = 1.9, shminux.U($10,000) = 2.1, and army1987.U($100,000) = shminux.U($100,000) = 3, then then I would prefer 50% probability of $1000 and 50% probability of $100,000 rather than 100% probability of $10,000, and you wouldn’t.