Computable Artificial General Intelligence
preprint
posted on 2022-05-31, 22:02 authored by Michael Timothy BennettMichael Timothy BennettAn 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.
History
Email Address of Submitting Author
michael.bennett@anu.edu.auORCID of Submitting Author
0000-0001-6895-8782Submitting Author's Institution
Australian National UniversitySubmitting Author's Country
- Australia