A-Life Evolution With Human Proxies

Recent successes in Artificial Intelligence (AI) use machine learning to produce AI agents with both hand-engineered and procedurally generated elements learned from large amounts of data. As the balance shifts toward procedural generation, how can we predict interactions between such agents and humans? We propose to use Artificial Life to study emergence of group behaviours between procedurally generated AI agents and humans. We simulate Darwinian evolution to procedurally generate agents in a simple environment where the agents interact with human-controlled avatars. To reduce human involvement time, we machine-learn another set of AI agents that mimic human avatar behaviours and run the evolution with such human proxies instead of actual humans. This paper is an update on the on-going project.