TY - JOUR
T1 - Autonomics
T2 - In search of a foundation for next-generation autonomous systems
AU - Harel, David
AU - Marron, Assaf
AU - Sifakis, Joseph
N1 - We are grateful to Guy Katz and Orna Kupferman for valuable discussions in the early stages of preparing the paper. This work was supported in part by grants to D.H. from the Israel Science Foundation, Intel Corporation, and the Estate of Emile Mimran, and from his endowed William Sussman Professorial Chair of Mathematics at the Weizmann Institute. This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected in 2019. Author contributions: D.H., A.M., and J.S. designed research, performed research, and wrote the paper.
PY - 2020/7/28
Y1 - 2020/7/28
N2 - 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.
AB - 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.
U2 - https://doi.org/10.1073/pnas.2003162117
DO - https://doi.org/10.1073/pnas.2003162117
M3 - مقالة
SN - 0027-8424
VL - 117
SP - 17491
EP - 17498
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 30
ER -