Well, you can talk about “what does decision theory W do in situation X” without specifying the likelyhood of other situations, by assuming that all agents start with a prior that sets P(X) = 1. In that case UDT clearly wins the anti-newcomb scenario because it knows that actual newcomb’s “never happens” and therefore it (counterfactually) two-boxes.
The only problem with this treatment is that in real life P(anti-newcomb) = 1 is an unrealistic model of the world, and you really should have a prior for P(anti-newcomb) vs P(newcomb). A decision theory that solves the restricted problem is not necessarily a good one for solving real life problems in general.
Well, perhaps. I think that the bigger problem is that under reasonable priors P(Newcomb) and P(anti-Newcomb) are both so incredibly small that I would have trouble finding a meaningful way to approximate their ratio.
How confident are you that UDT actually one-boxes?
Also yeah, if you want a better scenario where UDT loses see my PD against 99% prob. UDT and 1% prob. CDT example.
Well, you can talk about “what does decision theory W do in situation X” without specifying the likelyhood of other situations, by assuming that all agents start with a prior that sets P(X) = 1. In that case UDT clearly wins the anti-newcomb scenario because it knows that actual newcomb’s “never happens” and therefore it (counterfactually) two-boxes.
The only problem with this treatment is that in real life P(anti-newcomb) = 1 is an unrealistic model of the world, and you really should have a prior for P(anti-newcomb) vs P(newcomb). A decision theory that solves the restricted problem is not necessarily a good one for solving real life problems in general.
Well, perhaps. I think that the bigger problem is that under reasonable priors P(Newcomb) and P(anti-Newcomb) are both so incredibly small that I would have trouble finding a meaningful way to approximate their ratio.
How confident are you that UDT actually one-boxes?
Also yeah, if you want a better scenario where UDT loses see my PD against 99% prob. UDT and 1% prob. CDT example.