Introduction to open-world AI

Abstract

Open-world AI is characterized by sudden novel changes in a domain that are outside the scope of the training data, or the deployment of an agent in conditions that violate the implicit or explicit assumptions of the designer. In such situations, the AI system must detect the novelty and adapt in a short time frame. In this introduction to the special issue on open-world AI, we discuss the background and motivation for this new research area and define the field in the context of similar AI challenges. We then discuss recent research in the area that has made significant contributions to the field. Many of those contributions are reflected in the papers of this special issue, which we summarize alongside more traditional approaches to open-world AI. Finally, we discuss future directions for the field.