I’ve noticed that the Axiom of Independence does not seem to make sense when dealing with indexical uncertainty, which suggests that Expected Utility Theory may not apply in situations involving indexical uncertainty. But Googling for "indexical uncertainty" in combination with either "independence axiom" or “axiom of independence” give zero results, so either I’m the first person to notice this, I’m missing something, or I’m not using the right search terms. Maybe the LessWrong community can help me figure out which is the case.
The Axiom of Independence says that for any A, B, C, and p, you prefer A to B if and only if you prefer p A + (1-p) C to p B + (1-p) C. This makes sense if p is a probability about the state of the world. (In the following, I'll use “state” and “possible world” interchangeably.) In that case, what it’s saying is that what you prefer (e.g., A to B) in one possible world shouldn’t be affected by what occurs (C) in other possible worlds. Why should it, if only one possible world is actual?
In Expected Utility Theory, for each choice (i.e. option) you have, you iterate over the possible states of the world, compute the utility of the consequences of that choice given that state, then combine the separately computed utilities into an expected utility for that choice. The Axiom of Independence is what makes it possible to compute the utility of a choice in one state independently of its consequences in other states.
But what if p represents an indexical uncertainty, which is uncertainty about where (or when) you are in the world? In that case, what occurs at one location in the world can easily interact with what occurs at another location, either physically, or in one’s preferences. If there is physical interaction, then “consequences of a choice at a location” is ill-defined. If there is preferential interaction, then “utility of the consequences of a choice at a location” is ill-defined. In either case, it doesn’t seem possible to compute the utility of the consequences of a choice at each location separately and then combine them into a probability-weighted average.
Here’s another way to think about this. In the expression “p A + (1-p) C” that’s part of the Axiom of Independence, p was originally supposed to be the probability of a possible world being actual and A denotes the consequences of a choice in that possible world. We could say that A is local with respect to p. What happens if p is an indexical probability instead? Since there are no sharp boundaries between locations in a world, we can’t redefine A to be local with respect to p. And if A still denotes the global consequences of a choice in a possible world, then “p A + (1-p) C” would mean two different sets of global consequences in the same world, which is nonsensical.
If I’m right, the notion of a “probability of being at a location” will have to acquire an instrumental meaning in an extended decision theory. Until then, it’s not completely clear what people are really arguing about when they argue about such probabilities, for example in papers about the Simulation Argument and the Sleeping Beauty Problem.
Edit: Here's a game that exhibits what I call "preferential interaction" between locations. You are copied in your sleep, and both of you wake up in identical rooms with 3 buttons. Button A immunizes you with vaccine A, button B immunizes you with vaccine B. Button C has the effect of A if you're the original, and the effect of B if you're the clone. Your goal is to make sure at least one of you is immunized with an effective vaccine, so you press C.
To analyze this decision in Expected Utility Theory, we have to specify the consequences of each choice at each location. If we let these be local consequences, so that pressing A has the consequence "immunizes me with vaccine A", then what I prefer at each location depends on what happens at the other location. If my counterpart is vaccinated with A, then I'd prefer to be vaccinated with B, and vice versa. "immunizes me with vaccine A" by itself can't be assigned an utility.
What if we use the global consequences instead, so that pressing A has the consequence "immunizes both of us with vaccine A"? Then a choice's consequences do not differ by location, and “probability of being at a location” no longer has a role to play in the decision.
Thanks for adding an example. Let me rephrase it:
You have been invited to take part in a game theory experiment. You are placed in an empty room with three buttons labeled "1", "2" and "my room number". Another test subject is in another room with identical buttons. You don't know your room number, or theirs, but experimenters swear they're different. If you two press buttons corresponding to different numbers, you are both awarded $100 on exit, otherwise zero.
...What was so interesting about this problem, again?
It seems that my communication attempt failed badly last time, so let me try again. The "standard" approach to indexicals is to treat indexical uncertainty the same as any other kind of uncertainty. You compute a probability of being at each location, and then maximize expected utility. I tried to point out in this post that because decisions made at each location can interact non-linearly, this doesn't work.
You transformed my example into a game theory example, and the paradox disappeared, because game theory does take into account interactions ... (read more)