Journal Article

Autonomics: In search of a foundation for next-generation autonomous systems

Sifakis, Joseph, Marron, Assaf, Harel, David

2020

Overview

SignificanceAutonomous systems are replacing humans in a variety of tasks, and in the years to come, such systems will become central and crucial to human life. They will include vehicles of all kinds, medical and industrial robots, agricultural and manufacturing facilities, traffic management systems, and much more. While many organizations strive to develop the next generation of trustworthy, cost-effective autonomous systems, a major gap exists between the challenges in developing these and the state of the art. There is a crucial need for a common scientific and engineering foundation for developing these systems, which we term “autonomics.” We believe that such a foundation will dramatically accelerate the deployment and acceptance of high-quality autonomous systems, for the benefit of human society. 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 humans, 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.

• Publisher: National Academy of Sciences
• Subject: Artificial intelligence / Computer Sciences / Learning algorithms / Machine learning / Physical Sciences / Software engineering