Ravichandran, R;
Chong, C-Y;
Smith, RE;
(2021)
Artificial Intelligence and Machine Learning: A Perspective on Integrated Systems Opportunities and Challenges for Multi-Domain Operations.
In: Pham, T and Solomon, L, (eds.)
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III.
(pp. 1174606-1-1174606-17).
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Abstract
This paper provides a perspective on historical background, innovation and applications of Artificial Intelligence (AI) and Machine Learning (ML), data successes and systems challenges, national security interests, and mission opportunities for system problems. AI and ML today are used interchangeably, or together as AI/ML, and are ubiquitous among many industries and applications. The recent explosion, based on a confluence of new ML algorithms, large data sets, and fast and cheap computing, has demonstrated impressive results in classification and regression and used for prediction, and decision-making. Yet, AI/ML today lacks a precise definition, and as a technical discipline, it has grown beyond its origins in computer science. Even though there are impressive feats, primarily of ML, there still is much work needed in order to see the systems benefits of AI, such as perception, reasoning, planning, acting, learning, communicating, and abstraction. Recent national security interests in AI/ML have focused on problems including multidomain operations (MDO), and this has renewed the focus on a systems view of AI/ML. This paper will address the solutions for systems from an AI/ML perspective and that these solutions will draw from methods in AI and ML, as well as computational methods in control, estimation, communication, and information theory, as in the early days of cybernetics. Along with the focus on developing technology, this paper will also address the challenges of integrating these AI/ML systems for warfare.
| Type: | Proceedings paper |
|---|---|
| Title: | Artificial Intelligence and Machine Learning: A Perspective on Integrated Systems Opportunities and Challenges for Multi-Domain Operations |
| Event: | SPIE Defense and Commercial Sensing, 2021 |
| Dates: | 12 April 2021 - 16 April 2021 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.2587216 |
| Publisher version: | https://doi.org/10.1117/12.2587216 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Artificial Intelligence, machine learning, multi-domain operations, estimation, control, system of systems |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137430 |
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