AlephNeil comments on The Smoking Lesion: A problem for evidential decision theory - Less Wrong
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You're correct that if the correlation were known to be 100% then the only meaningful advice one could give would be not to smoke. However, it's important to understand that "100% correlation" is a degenerate case of the Smoking Lesion problem, as I'll try to explain:
Imagine a problem of the following form: Y is a variable under our control, which we can either set to k or -k for some k >= 0 (0 is not ruled out). X is an N(0, m^2) random variable which we do not observe, for some m >= 0 (again, 0 is not ruled out). Our payoff has the form (X + Y) - 1000(X + rY) for some constant r with 0 <= r <= 1. Working out the optimal strategy is rather trivial. But anyway, in the edge cases: If r = 0 we should put Y = k and if r = 1 we should put Y = -k.
Now I want to say that the case r = 0 is analogous to the Smoking Lesion problem and the case r = 1 is analogous to Newcomb's problem (with a flawless predictor):
ETA: Perhaps this analogy can be developed into an analysis of the original problems. One way to do it would be to define random variables Z and W taking values 0, 1 such that log(P(Z = 1 | X and Y)) / log(P(Z = 0 | X and Y)) = a linear combination of X and Y (and likewise for W, but with a different linear combination), and then have Z be the "player's decision" and W be "Omega's decision / whether person gets cancer". But I think the ratio of extra work to extra insight would be quite high.