Towards Sustainable Models of Computation for Artificial Intelligence in Cyber-Physical Systems
This paper confronts with a reflection about a deep problem in computational models for cyber-physical systems (CPS). The problem arises in the contact between digital computing and the physical realm, and affects heavily the design, modeling, and implementation of CPS. Problems are exacerbated by the introduction of artificial intelligence and autonomy in industrial applications that have to meet sustainability of solutions, both in technical and societal sense. After a brief review, a new perspective and position on the future of sustainable CPS is addressed, and a pragmatic research path is presented. The RMAS (Relational-model Multi-Agent System) architecture is proposed as a test framework for the deep integration of real-world semantics into the advancements brought about by the digital transformation wave.
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Towards Sustainable Models of Computation for Artificial Intelligence in Cyber-Physical Systems
Semantic Scholar · Computer Science · 2021
Abstract
This paper confronts with a reflection about a deep problem in computational models for cyber-physical systems (CPS). The problem arises in the contact between digital computing and the physical realm, and affects heavily the design, modeling, and implementation of CPS. Problems are exacerbated by the introduction of artificial intelligence and autonomy in industrial applications that have to meet sustainability of solutions, both in technical and societal sense. After a brief review, a new perspective and position on the future of sustainable CPS is addressed, and a pragmatic research path is presented. The RMAS (Relational-model Multi-Agent System) architecture is proposed as a test framework for the deep integration of real-world semantics into the advancements brought about by the digital transformation wave.