Objective Cyber-physical systems (CPS) are emerging throughout society, e.g. traffic systems, smart grids, smart cities, and medical devices, and brings the promise to society of better solutions in terms of performance, efficiency and usability. However, CPS are often highly safety critical, e.g. cars or medical devices, thus the utmost care must be taken that optimization of performance does not hamper crucial safety conditions. Given the constant growth in complexity of CPS, this task is becoming increasingly demanding for companies to handle with existing methods. The principle barrier for mastering the engineering of complex CPS being both trustworthy and efficient is the lack of a theoretical well-founded framework for CPS engineering supported by powerful tools, that will enable companies to timely meet increasing market demands.With his extensive contributions to model-driven methodologies, and as provider of one of the “foremost” tools for embedded systems verification, the PI is well prepared to provide the missing framework. The LASSO framework will support the quantitative modeling of both cyber- and physical components, their efficient analysis, the learning of models for unknown components, as well as automatic synthesis and optimization of missing cyber-components from specifications. LASSO will provide the new generation of scalable tools for CPS, allowing trade-offs between safety constraints and performance measure to be made.LASSO will achieve its objective by ground-breaking and extensive combinations of two different research areas: model checking and machine learning. The framework will develop a complete metric approximation theory for quantitative models, allowing properties to be inferred from reduced or learned models with metric guarantees of their validity in the original system. Further, the applicability of the framework will be validated through a number of CPS case studies, and the tools developed will be made generally available. Fields of science engineering and technologycivil engineeringurban engineeringsmart citiesengineering and technologyenvironmental engineeringwater treatment processeswastewater treatment processesengineering and technologyenvironmental engineeringenergy and fuelsrenewable energywind powerengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robotsdronesengineering and technologyenvironmental engineeringnatural resources managementwater management Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-ADG-2014 - ERC Advanced Grant Call for proposal ERC-2014-ADG See other projects for this call Funding Scheme ERC-ADG - Advanced Grant Coordinator AALBORG UNIVERSITET Net EU contribution € 2 493 750,00 Address Fredrik bajers vej 7k 9220 Aalborg Denmark See on map Region Danmark Nordjylland Nordjylland Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 1,25 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all AALBORG UNIVERSITET Denmark Net EU contribution € 2 493 750,00 Address Fredrik bajers vej 7k 9220 Aalborg See on map Region Danmark Nordjylland Nordjylland Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 1,25
