This is worth writing into its own post- a CDT agent with a non-self-centered utility function (like a paperclip maximizer) and a certain model of anthropics (in which, if it knows it’s being simulated, it views itself as possibly within the simulation), when faced with a Predictor that predicts by simulating (which is not always the case), one-boxes on Newcomb’s Problem.
This is a novel and surprising result in the academic literature on CDT, not the prediction they expected. But it seems to me that if you violate any of the conditions above, one-boxing collapses back into two-boxing; and furthermore, it won’t cooperate in the Prisoner’s Dilemma against a CDT agent with an orthogonal utility function. That, at least, is inescapable from the independence assumption.
This is worth writing into its own post- a CDT agent with a non-self-centered utility function (like a paperclip maximizer) and a certain model of anthropics (in which, if it knows it’s being simulated, it views itself as possibly within the simulation), when faced with a Predictor that predicts by simulating (which is not always the case), one-boxes on Newcomb’s Problem.
This is a novel and surprising result in the academic literature on CDT, not the prediction they expected. But it seems to me that if you violate any of the conditions above, one-boxing collapses back into two-boxing; and furthermore, it won’t cooperate in the Prisoner’s Dilemma against a CDT agent with an orthogonal utility function. That, at least, is inescapable from the independence assumption.