Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel;
Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Proc Natl Acad Sci U S A. 2020 Jul 28;117(30):17491-17498. doi: 10.1073/pnas.2003162117. Epub 2020 Jul 21.
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.
自主系统的潜在好处是显而易见的。然而,在开发此类系统成为一种常见的工程实践,并提供可接受和值得信赖的成果之前,仍有许多重大问题需要解决。我们认为,必须为开发下一代自主系统建立一个坚实、不断发展、公开可用、由社区控制的基础,我们将所需的基础称为“自主学”。我们重点关注三个主要挑战:1)如何在面对不可预测性的情况下指定自主系统的行为;2)如何对包含人类、物理制品和其他系统的丰富环境中的系统行为进行忠实分析;3)如何通过将软件工程中的可执行建模技术与人工智能和机器学习相结合来构建此类系统。