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?
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 ...
I am currently learning about the basics of decision theory, most of which is common knowledge on LW. I have a question, related to why EDT is said not to work.
Consider the following Newcomblike problem: A study shows that most people who two-box in Newcomblike problems as the following have a certain gene (and one-boxers don't have the gene). Now, Omega could put you into something like Newcomb's original problem, but instead of having run a simulation of you, Omega has only looked at your DNA: If you don't have the "two-boxing gene", Omega puts $1M into box B, otherwise box B is empty. And there is $1K in box A, as usual. Would you one-box (take only box B) or two-box (take box A and B)? Here's a causal diagram for the problem:
Since Omega does not do much other than translating your genes into money under a box, it does not seem to hurt to leave it out:
I presume that most LWers would one-box. (And as I understand it, not only CDT but also TDT would two-box, am I wrong?)
Now, how does this problem differ from the smoking lesion or Yudkowsky's (2010, p.67) chewing gum problem? Chewing Gum (or smoking) seems to be like taking box A to get at least/additional $1K, the two-boxing gene is like the CGTA gene, the illness itself (the abscess or lung cancer) is like not having $1M in box B. Here's another causal diagram, this time for the chewing gum problem:
As far as I can tell, the difference between the two problems is some additional, unstated intuition in the classic medical Newcomb problems. Maybe, the additional assumption is that the actual evidence lies in the "tickle", or that knowing and thinking about the study results causes some complications. In EDT terms: The intuition is that neither smoking nor chewing gum gives the agent additional information.