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Computable Artificial General Intelligence

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posted on 16.05.2022, 12:15 by Michael Timothy BennettMichael Timothy Bennett
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.

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Email Address of Submitting Author

michael.bennett@anu.edu.au

ORCID of Submitting Author

0000-0001-6895-8782

Submitting Author's Institution

Australian National University

Submitting Author's Country

Australia

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