On the intelligence of interacting autonomous robots and virtual agents

Abstract

This work explains some aspects why it is hard to pinpoint what intelligence is and more specifically, how to assess the intelligence of AI. It motivates a setup that is designed to foster the investigation of this question using reinforcement learning agents as complex AI systems. Such a setup can be used in an attempt to sidestep theoretical considerations on the cognitive power of Machine Learning algorithms. Instead, an example is given how the well-established experimental testing of intelligence in animals could be translated to the described AI system. While the published work-in-progress state of the implementation allows similar experiments of multiple interacting virtual robots to be conducted and a theoretical outline for future tests is sketched, a lot of further research will be required before a robot can demonstrably recognize itself in a mirror.