Artificial Intelligence for Systems Engineering - AI4SE 2020
13-14 October 2020
The Knowledge Reuse Group, INCOSE and AEIS invite submissions to AI4SE workshop, which will take place at Carlos III University of Madrid within the “Artificial Intelligence in Systems Engineering Week”.
Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence “demonstrated” by machines, in contrast to the natural intelligence displayed by humans and animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chances of successfully achieving its goals. Colloquially, the term "artificial intelligence" is used to describe machines that mimic certain "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".
Systems Engineering (SE) is an interdisciplinary field of engineering development and engineering management that focuses on how to design and manage complex systems throughout their life cycle. Activities such as requirements engineering, reliability management, logistics, coordination of different teams, testing and evaluation, maintainability and many other disciplines necessary for the successful development, design, implementation, and ultimate decommission of systems, become more difficult when dealing with large or complex projects.
Topics of interest:
Many of the challenges described in the previous definitions are human intensive, and could demand highly developed skills in learning, reasoning, decision making and problem solving. Therefore, Artificial Intelligence and all of its interleaved variants (machine learning, knowledge engineering, artificial reasoning, ontologies, optimization methods, etc.) are more and more relevant to systems engineering.
On the other hand, emergent Intelligent Systems like autonomous vehicles in all their facets (cars, trains, submarines, aircrafts, ships, etc.) are revolutionizing our perception of services. These systems are offering divergent ways of operations, where machines learn from their own operation and, theoretically, they improve its quality of service. Not deterministic systems propose giant challenges like how the certification should take place considering they will operate differently along its service life. How to V&V them, or even how to configure them in the case of potential accidents, ethical aspects etc.
For more information, for the workshop visit the website and see the AI4SE 2020 Call for Papers.