Open Problems in Universal Induction & Intelligence

TL;DR

This paper reviews the recent advances in the mathematical theory of universal induction and intelligence, highlighting open problems and future directions in the foundational understanding of artificial intelligence.

Contribution

It identifies unresolved issues in the theory of universal induction and its extension to universal intelligence, emphasizing the need for further research in this foundational area.

Findings

Universal induction provides a solid theoretical foundation for AI.

The theory has been developed over the past decades, but key open problems remain.

The article highlights the importance of addressing these open problems for future progress.

Abstract

Specialized intelligent systems can be found everywhere: finger print, handwriting, speech, and face recognition, spam filtering, chess and other game programs, robots, et al. This decade the first presumably complete mathematical theory of artificial intelligence based on universal induction-prediction-decision-action has been proposed. This information-theoretic approach solidifies the foundations of inductive inference and artificial intelligence. Getting the foundations right usually marks a significant progress and maturing of a field. The theory provides a gold standard and guidance for researchers working on intelligent algorithms. The roots of universal induction have been laid exactly half-a-century ago and the roots of universal intelligence exactly one decade ago. So it is timely to take stock of what has been achieved and what remains to be done. Since there are already good recent surveys, I describe the state-of-the-art only in passing and refer the reader to the literature. This article concentrates on the open problems in universal induction and its extension to universal intelligence.