Are you saying that it’s easier to get TDT to comply to CM if it’s ontologically fundamental randomness than if it’s logical uncertainty? (but you think it can be made to comply then, too)
In the least convenient possible world, the TDT agent doesn’t care intrinsically about any counterfactual process, only about the result on the real world.
Saying you can get an agent with one DT to follow the output of another DT by changing its utility function is not interesting.
Saying you can get an agent with one DT to follow the output of another DT by changing its utility function is not interesting.
If the mapping is natural enough, it establishes relative expressive power of the decision theories, perhaps even allowing to get the same not-a-priori-obvious conclusions from studying one theory as the other. But granted, as I described in this post, the step forward made in UDT/ADT, as compared to TDT, is that causal graph doesn’t need to be given as part of problem statement, dependencies get inferred from utility/action definition.
I am not following your abstract argument, and would like to see an example of how a “natural enough” mapping can establish “relative expressive power of the decision theories”.
Not if it expresses what’s real, but surely if it expresses what the agent cares about, basically the counterfactual world explicitly included.
Are you saying that it’s easier to get TDT to comply to CM if it’s ontologically fundamental randomness than if it’s logical uncertainty? (but you think it can be made to comply then, too)
In the least convenient possible world, the TDT agent doesn’t care intrinsically about any counterfactual process, only about the result on the real world.
Saying you can get an agent with one DT to follow the output of another DT by changing its utility function is not interesting.
If the mapping is natural enough, it establishes relative expressive power of the decision theories, perhaps even allowing to get the same not-a-priori-obvious conclusions from studying one theory as the other. But granted, as I described in this post, the step forward made in UDT/ADT, as compared to TDT, is that causal graph doesn’t need to be given as part of problem statement, dependencies get inferred from utility/action definition.
Ok, so show me an actual example of a mapping that is “natural enough”, and causes TDT to pay of in CM.
I argued with your argument, not your conclusion.
I am not following your abstract argument, and would like to see an example of how a “natural enough” mapping can establish “relative expressive power of the decision theories”.