System induction games and cognitive modeling as an AGI methodology

Abstract

We propose a methodology for using human cognition as a template for artificial generally intelligent agents that learn from experience. In particular, we consider the problem of learning certain Mealy machines from observations of their behavior; this is a general but conceptually simple learning task that can be given to humans as well as machines. We illustrate by example the sorts of observations that can be gleaned from studying human performance on this task.