Applications of Algorithmic Probability to the Philosophy of Mind
It addresses foundational philosophical conundrums for researchers in AI and philosophy, though it is incremental in combining existing formalisms.
The paper tackles philosophical problems like the simulation argument and mind-uploading by applying algorithmic probability and universal intelligence measures, proposing that universal models can provide ultimate solutions but require computationally efficient approximations.
This paper presents formulae that can solve various seemingly hopeless philosophical conundrums. We discuss the simulation argument, teleportation, mind-uploading, the rationality of utilitarianism, and the ethics of exploiting artificial general intelligence. Our approach arises from combining the essential ideas of formalisms such as algorithmic probability, the universal intelligence measure, space-time-embedded intelligence, and Hutter's observer localization. We argue that such universal models can yield the ultimate solutions, but a novel research direction would be required in order to find computationally efficient approximations thereof.