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SEMANTICALLY‐ENABLED MODEL‐BASED SYSTEMS
Author(s) -
Petnga Leonard,
Austin Mark,
Blackburn Mark
Publication year - 2017
Publication title -
insight
Language(s) - English
Resource type - Journals
eISSN - 2156-4868
pISSN - 2156-485X
DOI - 10.1002/inst.12161
Subject(s) - computer science , executable , intersection (aeronautics) , ambiguity , domain (mathematical analysis) , encode , semantics (computer science) , metamodeling , software engineering , domain knowledge , theoretical computer science , artificial intelligence , programming language , engineering , mathematical analysis , biochemistry , chemistry , mathematics , gene , aerospace engineering
This paper describes a novel approach to the development and integration of semantics to the model‐based systems engineering and operation of safety‐critical network of systems. Engineering models work directly with formal domain and meta‐domain (especially time and space) knowledge that are determinate, provable (ambiguity free), and executable. Engineers encode knowledge as semantic blocks, which are an integration of ontologies, rules, and communication and computation interfaces. This paper exercises these concepts in a collision avoidance problem involving autonomous agents at a traffic intersection.