  Autonomous agents acting in real-world environments often need to reason with
unknown novelties interfering with their plan execution. Novelty is an
unexpected phenomenon that can alter the core characteristics, composition, and
dynamics of the environment. Novelty can occur at any time in any sufficiently
complex environment without any prior notice or explanation. Previous studies
show that novelty has catastrophic impact on agent performance. Intelligent
agents reason with an internal model of the world to understand the intricacies
of their environment and to successfully execute their plans. The introduction
of novelty into the environment usually renders their internal model inaccurate
and the generated plans no longer applicable. Novelty is particularly prevalent
in the real world where domain-specific and even predicted novelty-specific
approaches are used to mitigate the novelty's impact. In this work, we
demonstrate that a domain-independent AI agent designed to detect,
characterize, and accommodate novelty in smaller-scope physics-based games such
as Angry Birds and Cartpole can be adapted to successfully perform and reason
with novelty in realistic high-fidelity simulator of the military domain.
