The trouble is that it’s tricky to apply a single decision theory to this problem, because by hypothesis, this gene actually changes which decision theory you use! If I’m a TDT agent, then this is good evidence I have the “TDT-agent gene,” but in this problem I don’t actually know whether the TDT-gene is the one-box gene or the two-box gene. If TDT leads to one-boxing, then it recommends two-boxing—but if it provably two-boxes it is the “two-box gene” and gets the bad outcome. This is to some extent an “evil decision problem.” Currently I’d one-box, based on some notion of resolving these sorts of problems through more UDT-ish proof-based reasoning (though it has some problems). Or in TDT-language, I’d be ‘controlling’ whether the TDT-gene was the two-box gene by picking the output of TDT.
However, this problem becomes a lot easier if most people are not actually using any formal reasoning, but are just doing whatever seems like a good idea at the time. Like, the sort of reasoning that leads to people actually smoking. If I’m dropped into this genetic Newcomb’s problem, or into the smoking lesion problem, and I learn that almost all people in the data set I’ve seen were either bad at decision theory or didn’t know the results of the data, then those people no longer have quite the same evidential impact about my current situation, and I can just smoke / two-box. It’s only when those people and myself are in symmetrical situations (similar information, use similar decision-making processes) that I have to “listen” to them.
I am not entirely sure, I understand your TDT analysis, maybe that’s because I don’t understand TDT that well. I assumed that TDT would basically just do what CDT does, because there are no simulations of the agent involved. Or do you propose that checking for the gene is something like simulating the agent?
This is to some extent an “evil decision problem.”
It does not seem to be more evil than Newcomb’s problem, but I am not sure, what you mean by “evil”. For every decision theory, it is possible, of course, to set up some decision problem, where this decision theory loses. Would you say that I set up the “genetic Newcomb problem” specifically to punish CDT/TDT?
because there are no simulations of the agent involved.
The role that would normally be played by simulation is here played by a big evidential study of what people with different genes do. This is why it matters whether the people in the study are good decision-makers or not—only when the people in the study are in a position similar to my own do they fulfill this simulation-like role.
It does not seem to be more evil than Newcomb’s problem, but I am not sure, what you mean by “evil”. For every decision theory, it is possible, of course, to set up some decision problem, where this decision theory loses. Would you say that I set up the “genetic Newcomb problem” specifically to punish CDT/TDT?
Yeah, that sentence is phrased poorly, sorry. But I’ll try to explain. The easy way to construct an evil decision problem (say, targeting TDT) is to figure out what action TDT agents take, and then set the hidden variables so that that action is suboptimal—in this way the problem can be tilted against TDT agents even if the hidden variables don’t explicitly care that their settings came from this evil process.
In this problem, the “gene” is like a flag on a certain decision theory that tells what action it will take, and the hidden variables are set such that people with that decision theory (the decision theory that people with the one-box gene use) act suboptimally (people with the one-box gene who two-box get more money). So this uses very similar machinery to an evil decision problem. The saving grace is that the other action also gets its own flag (the two-box gene), which has a different setting of the hidden variables.
The role that would normally be played by simulation is here played by a big evidential study of what people with different genes do. This is why it matters whether the people in the study are good decision-makers or not—only when the people in the study are in a position similar to my own do they fulfill this simulation-like role.
Yes, the idea is that they are sufficiently similar to you so that the study can be applied (but also sufficiently different to make it counter-intuitive to say it’s a simulation). The subjects of the study may be told that there already exists a study, so that their situation is equivalent to yours. It’s meant to be similar to the medical Newcomb problems in that regard.
I briefly considered the idea that TDT would see the study as a simulation, but discarded the possibility, because in that case the studies in classic medical Newcomb problems could also be seen as simulations of the agent to some degree. The “abstract computation that an agent implements” is a bit vague, anyway, I assume, but if one were willing to go this far, is it possible that TDT conflates with EDT?
Under the formulation that leads to one-boxing here, TDT will be very similar to EDT whenever the evidence is about the unknown output of your agent’s decision problem. They are both in some sense trying to “join the winning team”—EDT by expecting the winning-team action to make them have won, and TDT only in problems where what team you are on is identical to what action you take.
This is not an “evil decision problem” for the same reason original Newcomb is not, namely that whoever chooses only one box gets the reward, not matter what process he uses.
Yes, all of this is basically correct. However, it is also basically the same in the original Newcomb although somewhat more intuitive. In the original problem Omega decides to put the one million or not depending on its estimate of what you will do, which likely depends on “what kind of person” you are, in some sense. And being this sort of person is also going to determine what kind of decision theory you use, just as the gene does in the genetic version. The original Newcomb is more intuitive, though, because we can more easily accept that “being such and such a kind of person” could make us use a certain decision theory, than that a gene could do the same thing.
Even the point about other people knowing the results or using certain reasoning is the same. If you find an Omega in real life, but find out that all the people being tested so far are not using any decision theory, but just choosing impulsively, and Omega is just judging how they would choose impulsively, then you should take both boxes. It is only if you know that Omega tends to be right no matter what decision theory people are using, that you should choose the one box.
Hm, this is a really interesting idea.
The trouble is that it’s tricky to apply a single decision theory to this problem, because by hypothesis, this gene actually changes which decision theory you use! If I’m a TDT agent, then this is good evidence I have the “TDT-agent gene,” but in this problem I don’t actually know whether the TDT-gene is the one-box gene or the two-box gene. If TDT leads to one-boxing, then it recommends two-boxing—but if it provably two-boxes it is the “two-box gene” and gets the bad outcome. This is to some extent an “evil decision problem.” Currently I’d one-box, based on some notion of resolving these sorts of problems through more UDT-ish proof-based reasoning (though it has some problems). Or in TDT-language, I’d be ‘controlling’ whether the TDT-gene was the two-box gene by picking the output of TDT.
However, this problem becomes a lot easier if most people are not actually using any formal reasoning, but are just doing whatever seems like a good idea at the time. Like, the sort of reasoning that leads to people actually smoking. If I’m dropped into this genetic Newcomb’s problem, or into the smoking lesion problem, and I learn that almost all people in the data set I’ve seen were either bad at decision theory or didn’t know the results of the data, then those people no longer have quite the same evidential impact about my current situation, and I can just smoke / two-box. It’s only when those people and myself are in symmetrical situations (similar information, use similar decision-making processes) that I have to “listen” to them.
I am not entirely sure, I understand your TDT analysis, maybe that’s because I don’t understand TDT that well. I assumed that TDT would basically just do what CDT does, because there are no simulations of the agent involved. Or do you propose that checking for the gene is something like simulating the agent?
It does not seem to be more evil than Newcomb’s problem, but I am not sure, what you mean by “evil”. For every decision theory, it is possible, of course, to set up some decision problem, where this decision theory loses. Would you say that I set up the “genetic Newcomb problem” specifically to punish CDT/TDT?
The role that would normally be played by simulation is here played by a big evidential study of what people with different genes do. This is why it matters whether the people in the study are good decision-makers or not—only when the people in the study are in a position similar to my own do they fulfill this simulation-like role.
Yeah, that sentence is phrased poorly, sorry. But I’ll try to explain. The easy way to construct an evil decision problem (say, targeting TDT) is to figure out what action TDT agents take, and then set the hidden variables so that that action is suboptimal—in this way the problem can be tilted against TDT agents even if the hidden variables don’t explicitly care that their settings came from this evil process.
In this problem, the “gene” is like a flag on a certain decision theory that tells what action it will take, and the hidden variables are set such that people with that decision theory (the decision theory that people with the one-box gene use) act suboptimally (people with the one-box gene who two-box get more money). So this uses very similar machinery to an evil decision problem. The saving grace is that the other action also gets its own flag (the two-box gene), which has a different setting of the hidden variables.
Yes, the idea is that they are sufficiently similar to you so that the study can be applied (but also sufficiently different to make it counter-intuitive to say it’s a simulation). The subjects of the study may be told that there already exists a study, so that their situation is equivalent to yours. It’s meant to be similar to the medical Newcomb problems in that regard.
I briefly considered the idea that TDT would see the study as a simulation, but discarded the possibility, because in that case the studies in classic medical Newcomb problems could also be seen as simulations of the agent to some degree. The “abstract computation that an agent implements” is a bit vague, anyway, I assume, but if one were willing to go this far, is it possible that TDT conflates with EDT?
Under the formulation that leads to one-boxing here, TDT will be very similar to EDT whenever the evidence is about the unknown output of your agent’s decision problem. They are both in some sense trying to “join the winning team”—EDT by expecting the winning-team action to make them have won, and TDT only in problems where what team you are on is identical to what action you take.
This is not an “evil decision problem” for the same reason original Newcomb is not, namely that whoever chooses only one box gets the reward, not matter what process he uses.
Yes, all of this is basically correct. However, it is also basically the same in the original Newcomb although somewhat more intuitive. In the original problem Omega decides to put the one million or not depending on its estimate of what you will do, which likely depends on “what kind of person” you are, in some sense. And being this sort of person is also going to determine what kind of decision theory you use, just as the gene does in the genetic version. The original Newcomb is more intuitive, though, because we can more easily accept that “being such and such a kind of person” could make us use a certain decision theory, than that a gene could do the same thing.
Even the point about other people knowing the results or using certain reasoning is the same. If you find an Omega in real life, but find out that all the people being tested so far are not using any decision theory, but just choosing impulsively, and Omega is just judging how they would choose impulsively, then you should take both boxes. It is only if you know that Omega tends to be right no matter what decision theory people are using, that you should choose the one box.