Algorithmic idealism: what should you believe to experience next?

• URL: http://arxiv.org/abs/2412.02826v1
• Date: Tue, 03 Dec 2024 20:44:32 GMT
• Title: Algorithmic idealism: what should you believe to experience next?
• Authors: Markus P. Mueller,
• Abstract summary: I argue for an approach to the Foundations of Physics that puts the question in the title center stage, rather than asking "what is the case in the world?"<n>Algorithmic Idealism is a conceptual framework, based on two postulates that admit several possible mathematical formalizations.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: I argue for an approach to the Foundations of Physics that puts the question in the title center stage, rather than asking "what is the case in the world?". This approach, Algorithmic Idealism, attempts to give a mathematically rigorous in-principle-answer to this question both in the usual empirical regime of physics and more exotic regimes of cosmology, philosophy, and science fiction (but soon perhaps real) technology. I begin by arguing that quantum theory, in its actual practice and in some interpretations, should be understood as telling an agent what they should expect to observe next (rather than what is the case), and that the difficulty of answering this former question from the usual "external" perspective is at the heart of persistent enigmas such as the Boltzmann brain problem, extended Wigner's friend scenarios, Parfit's teletransportation paradox, or our understanding of the simulation hypothesis. Algorithmic Idealism is a conceptual framework, based on two postulates that admit several possible mathematical formalizations, cast in the language of algorithmic information theory. Here I give a non-technical description of this view and show how it dissolves the aforementioned enigmas: for example, it claims that you should never bet on being a Boltzmann brain regardless of how many there are, that shutting down computer simulations does not generally terminate its inhabitants, and it predicts the apparent embedding into an objective external world as an approximate description.

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