I see. I suppose you’d do this by creating a policy node that is subjunctively upstream of every individual FDT decision, and intervening on that. The possible values would be every combination of FDT decisions, and you’d calculate updateless expected value over them.
This seems to work, though I’ll think on it some more. I’m a little disappointed that this isn’t the formulation of FDT in the paper, since that feels like a pretty critical distinction. But in any case, I should have read more carefully, so that’s on me. Thank you for bringing that up! Your comment is now linked in the introduction :)
I see. I suppose you’d do this by creating a policy node that is subjunctively upstream of every individual FDT decision, and intervening on that. The possible values would be every combination of FDT decisions, and you’d calculate updateless expected value over them.
This seems to work, though I’ll think on it some more. I’m a little disappointed that this isn’t the formulation of FDT in the paper, since that feels like a pretty critical distinction. But in any case, I should have read more carefully, so that’s on me. Thank you for bringing that up! Your comment is now linked in the introduction :)