The potential benefits of autonomous systems are obvious. However, there are still major issues to be dealt with before developing such systems becomes a commonplace engineering practice, with accepted and trustworthy deliverables. We argue that a solid, evolving, publicly available, community-controlled foundation for developing next-generation autonomous systems is a must, and term the desired foundation "autonomics." We focus on three main challenges: 1) how to specify autonomous system behavior in the face of unpredictability; 2) how to carry out faithful analysis of system behavior with respect to rich environments that include hu-mans, physical artifacts, and other systems; and 3) how to build such systems by combining executable modeling techniques from software engineering with artificial intelligence and machine learning.
|Number of pages||8|
|Journal||Proceedings of the National Academy of Sciences of the United States of America|
|State||Published - 28 Jul 2020|