What I mean is that for EDT agents in the population that are in this scenario, there will be zero correlation, and the agents should be able to deduce that and therefore smoke.
Whether there is a positive correlation among people who aren’t in this type of scenario or aren’t EDT agents should be irrelevant to any EDT agents.
More precisely: The factor P(outcome | action, known information) in the EDT formula is not the same thing as P(outcome | action, some prior or other) and yet the correlation stated in the scenario setup is of the latter form. The calculation that supposedly leads an EDT agent to refrain from smoking is incorrect due to this. The agent would have to ignore known information to arrive at the supposed conclusion.
What I mean is that for EDT agents in the population that are in this scenario, there will be zero correlation, and the agents should be able to deduce that and therefore smoke.
Whether there is a positive correlation among people who aren’t in this type of scenario or aren’t EDT agents should be irrelevant to any EDT agents.
More precisely: The factor P(outcome | action, known information) in the EDT formula is not the same thing as P(outcome | action, some prior or other) and yet the correlation stated in the scenario setup is of the latter form. The calculation that supposedly leads an EDT agent to refrain from smoking is incorrect due to this. The agent would have to ignore known information to arrive at the supposed conclusion.
Hmmm. You are probably right.