# Are there other mathematical frameworks of artificial general intelligence apart from AIXI?

AIXI is a mathematical framework for artificial general intelligence developed by Marcus Hutter since the year 2000. It's based on many concepts, such as reinforcement learning, Bayesian statistics, Occam's razor, or Solomonoff induction. The blog post What is AIXI? — An Introduction to General Reinforcement Learning provides an accessible overview of the topic for those of you not familiar with it.

Are there any other mathematical frameworks of artificial general intelligence apart from AIXI?

I am aware of projects such as OpenCog, but that's not really a mathematical framework, but more a cognitive science framework.

The initial proof searcher is $$O$$()-optimal (has an optimal order of complexity) in the sense of Theorem 5.1, Section 5. Unlike hardwired systems such as Hutter's and Levin's (Section 6.4), however, a Gödel machine can in principle speed up any part of its initial software, including its proof searcher, to meet arbitrary formalizable notions of optimality beyond those expressible in the $$O$$()-notation. Our approach yields the first theoretically sound, fully self-referential, optimal, general problem solvers.