This is also isomorphic to the absent-minded driver problem with different utilities (and mixed strategies*), it seems. Specifically, if you consider the abstract idealized decision theory you implement to be “you”, you make the same decision in two places, once in omega’s brain while he predicts you and again if he asks you to pay up. Therefore the graph can be transformed from this
into this
which looks awfully like the absent minded driver. Interesting.
Additionally, modifying the utilities involved ($1000 → death; swap -$100 and $0) gives Parfit’s Hitchhiker.
Looks like this isn’t really a new decision theory problem at all.
*ETA: Of course mixed strategies are allowed, if Omega is allowed to be an imperfect predictor. Duh. Clearly I wasn’t paying proper attention...
The common dynamic across all these problems is that “You could have been in a winning or losing branch, but you’ve learned that you’re in a losing branch, and your decision to scrape out a little more utility within that branch takes away more utility from (symmetric) versions of yourself in (potentially) winning branches.”
Disagree. In e.g. the case of hazing, the person who has hazed me is not a counterfactual me, and his decision is not sufficiently correlated with my own for this approach to apply.
Whether it’s a counterfactual you is less important than whether it’s a symmetric version of you with the same incentives and preferences. And the level of correlation is not independent of whether you believe there’s a correlation (like on Newcomb’s problem and PD).
Yes, depending on the situation, there may be in intractable discorrelation as you move from the idealization to real-world hazing.
But keep in mind, even if the agents actually were fully correlated (as specified in my phrasing of the Hazing Problem), they could still condemn themselves to perpetual hazing as a result of using a decision theory that returns a different output depending what branch you have learned you are in, and it is this failure that you want to avoid.
There’s a difference between believing that a particular correlation is poor, vs. believing that only outcomes within the current period matter for your decision.
(Side note: this relates to the discussion of the CDT blind spot on page 51 of EY’s TDT paper.)
Does this depend on many worlds as talking about “branches” seems to suggest? Consider, e.g.
You could have won or lost this time, but you’ve learned that you’ve lost, and your decision to scrape out a little more utility in this case takes away more utility by increasing the chance of losing in future similar situations.
The problems are set up as one-shot so you can’t appeal to a future chance of (yourself experiencing) losing that is caused by this decision. By design, the problems probe your theory of identity and what you should count as relevant for purposes of decision-making.
“You could have been in a winning or losing branch, but you’ve learned that you’re in a losing branch, and your decision to scrape out a little more utility within that branch takes away more utility from (symmetric) versions of yourself in (potentially) winning branches.”
In the Hitchhiker you’re scraping in the winning branch though.
True, I didn’t mean the isomorphism to include that problem, but rather, just the ones I mentioned plus counterfactual mugging and (if I understand the referent correctly) the transparent box newcomb’s. Sorry if I wasn’t clear.
Looks like this isn’t really a new decision theory problem at all.
Sort of. The shape is old, the payoffs are new. If Parfit’s Hitchhiker, you pay for not being counterfactually cast into the left branch. In Extremely Counterfactual Mugging, you pay for counterfactually gaining access to the left branch.
This is also isomorphic to the absent-minded driver problem with different utilities (and mixed strategies*), it seems. Specifically, if you consider the abstract idealized decision theory you implement to be “you”, you make the same decision in two places, once in omega’s brain while he predicts you and again if he asks you to pay up. Therefore the graph can be transformed from this
into this
which looks awfully like the absent minded driver. Interesting.
Additionally, modifying the utilities involved ($1000 → death; swap -$100 and $0) gives Parfit’s Hitchhiker.
Looks like this isn’t really a new decision theory problem at all.
*ETA: Of course mixed strategies are allowed, if Omega is allowed to be an imperfect predictor. Duh. Clearly I wasn’t paying proper attention...
I contend it’s also isomorphic to the very real-world problems of hazing, abuse cycles, and akrasia.
The common dynamic across all these problems is that “You could have been in a winning or losing branch, but you’ve learned that you’re in a losing branch, and your decision to scrape out a little more utility within that branch takes away more utility from (symmetric) versions of yourself in (potentially) winning branches.”
Disagree. In e.g. the case of hazing, the person who has hazed me is not a counterfactual me, and his decision is not sufficiently correlated with my own for this approach to apply.
Whether it’s a counterfactual you is less important than whether it’s a symmetric version of you with the same incentives and preferences. And the level of correlation is not independent of whether you believe there’s a correlation (like on Newcomb’s problem and PD).
Incentives, preferences, and decision procedure. Mine are not likely to be highly correlated with a random hazer’s.
Yes, depending on the situation, there may be in intractable discorrelation as you move from the idealization to real-world hazing.
But keep in mind, even if the agents actually were fully correlated (as specified in my phrasing of the Hazing Problem), they could still condemn themselves to perpetual hazing as a result of using a decision theory that returns a different output depending what branch you have learned you are in, and it is this failure that you want to avoid.
There’s a difference between believing that a particular correlation is poor, vs. believing that only outcomes within the current period matter for your decision.
(Side note: this relates to the discussion of the CDT blind spot on page 51 of EY’s TDT paper.)
This is very nicely put.
Does this depend on many worlds as talking about “branches” seems to suggest? Consider, e.g.
No. These branches correspond to the branches in diagrams.
Ah, i see. That makes much more sense. Thanks.
The problems are set up as one-shot so you can’t appeal to a future chance of (yourself experiencing) losing that is caused by this decision. By design, the problems probe your theory of identity and what you should count as relevant for purposes of decision-making.
Also, what Bongo said.
In the Hitchhiker you’re scraping in the winning branch though.
True, I didn’t mean the isomorphism to include that problem, but rather, just the ones I mentioned plus counterfactual mugging and (if I understand the referent correctly) the transparent box newcomb’s. Sorry if I wasn’t clear.
Sort of. The shape is old, the payoffs are new. If Parfit’s Hitchhiker, you pay for not being counterfactually cast into the left branch. In Extremely Counterfactual Mugging, you pay for counterfactually gaining access to the left branch.