Can CDT rationalise the ex ante optimal policy via modified anthropics?

Fuente: arXiv
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Autores principales: Cooper, Emery, Oesterheld, Caspar, Conitzer, Vincent
Formato: Preprint
Publicado: 2024
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author Cooper, Emery
Oesterheld, Caspar
Conitzer, Vincent
author_facet Cooper, Emery
Oesterheld, Caspar
Conitzer, Vincent
contents In Newcomb's problem, causal decision theory (CDT) recommends two-boxing and thus comes apart from evidential decision theory (EDT) and ex ante policy optimisation (which prescribe one-boxing). However, in Newcomb's problem, you should perhaps believe that with some probability you are in a simulation run by the predictor to determine whether to put a million dollars into the opaque box. If so, then causal decision theory might recommend one-boxing in order to cause the predictor to fill the opaque box. In this paper, we study generalisations of this approach. That is, we consider general Newcomblike problems and try to form reasonable self-locating beliefs under which CDT's recommendations align with an EDT-like notion of ex ante policy optimisation. We consider approaches in which we model the world as running simulations of the agent, and an approach not based on such models (which we call 'Generalised Generalised Thirding', or GGT). For each approach, we characterise the resulting CDT policies, and prove that under certain conditions, these include the ex ante optimal policies.
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id arxiv_https___arxiv_org_abs_2411_04462
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Can CDT rationalise the ex ante optimal policy via modified anthropics?
Cooper, Emery
Oesterheld, Caspar
Conitzer, Vincent
Artificial Intelligence
Computer Science and Game Theory
In Newcomb's problem, causal decision theory (CDT) recommends two-boxing and thus comes apart from evidential decision theory (EDT) and ex ante policy optimisation (which prescribe one-boxing). However, in Newcomb's problem, you should perhaps believe that with some probability you are in a simulation run by the predictor to determine whether to put a million dollars into the opaque box. If so, then causal decision theory might recommend one-boxing in order to cause the predictor to fill the opaque box. In this paper, we study generalisations of this approach. That is, we consider general Newcomblike problems and try to form reasonable self-locating beliefs under which CDT's recommendations align with an EDT-like notion of ex ante policy optimisation. We consider approaches in which we model the world as running simulations of the agent, and an approach not based on such models (which we call 'Generalised Generalised Thirding', or GGT). For each approach, we characterise the resulting CDT policies, and prove that under certain conditions, these include the ex ante optimal policies.
title Can CDT rationalise the ex ante optimal policy via modified anthropics?
topic Artificial Intelligence
Computer Science and Game Theory
url https://arxiv.org/abs/2411.04462