GOLEM: Towards an AGI meta-architecture enabling both goal preservation and radical self-improvement

Abstract

A high-level AGI architecture called GOLEM (Goal-Oriented LEarning Meta-Architecture) is presented, along with an informal but careful argument that GOLEM may be capable of preserving its initial goals while radically improving its general intelligence. As a meta-architecture, GOLEM can be wrapped around a variety of different base-level AGI systems, and also has a role for a powerful narrow-AI subcomponent as a probability estimator. The motivation underlying these ideas is the desire to create AGI systems fulfilling the multiple criteria of being: massively and self-improvingly intelligent; probably beneficial; and almost surely not destructive.