A Novelty Centric Agent Architecture for Changing Worlds

Open-world AI requires artificial agents to cope with novelties that arise during task performance, i.e., they must (1) detect novelties, (2) characterize them, in order to (3) accommodate them, especially in cases where sudden changes to the environment make task accomplishment impossible without utilizing the novelty. We present a formal framework and implementation thereof in a cognitive agent for novelty handling and demonstrate the efficacy of the proposed methods for detecting and handling a large set of novelties in a crafting task in a simulated environment. We discuss the success of the proposed knowledge-based methods and propose heuristic extensions that will further improve novelty handling in open-worlds tasks