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Computable Artificial General Intelligence

2022-05-21 06:32:09
Michael Timothy Bennett
arXiv_AI
         
Abstract

An artificial general intelligence (AGI), by one definition, is an agent that requires less information than any other to make an accurate prediction. It is arguable that the general reinforcement learning agent AIXI not only met this definition, but was the only mathematical formalism to do so. Though a significant result, AIXI was incomputable and its performance subjective. This paper proposes an alternative formalism of AGI which overcomes both problems. Formal proof of its performance is given, along with a simple implementation and experimental results that support these claims.

Abstract (translated)

URL

https://arxiv.org/abs/2205.10513

PDF

https://arxiv.org/pdf/2205.10513.pdf

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