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Towards a Research Agenda for Understanding and Managing Uncertainty in Self-Adaptive Systems
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- Danny Weyns
- KU Leuven
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- Radu Calinescu
- University of York
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- Raffaela Mirandola
- Politecnico di Milano
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- Kenji Tei
- Waseda University
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- Maribel Acosta
- Ruhr University Bochum
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- Nelly Bencomo
- Durham University
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- Amel Bennaceur
- The Open University
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- Nicolas Boltz
- Karlsruhe Institute of Technology
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- Tomas Bures
- Charles University, Prague
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- Javier Camara
- Universidad de Málaga
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- Ada Diaconescu
- Télécom Paris, Paris, France
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- Gregor Engels
- Paderborn University
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- Simos Gerasimou
- University of York
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- Ilias Gerostathopoulos
- Vrije Universiteit Amsterdam
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- Sinem Getir Yaman
- University of York
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- Vincenzo Grassi
- Università di Roma
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- Sebastian Hahner
- Karlsruhe Institute of Technology
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- Paola Inverardi
- Gran Sasso Science Institute
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- Dimitri Van Landuyt
- KU Leuven
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- Rogerio de Lemos
- University of Kent
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- Emmanuel Letier
- University College London
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- Marin Litoiu
- York University
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- Lina Marsso
- University of Toronto
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- Angelika Musil
- KU Leuven
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- Juergen Musil
- CDL-SQI, TU Wien
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- Genaina Nunes Rodrigues
- University of Brasília
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- Diego Perez-Palacin
- Linnaeus University
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- Federico Quin
- KU Leuven
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- Patrizia Scandurra
- University of Bergamo
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- Antonio Vallecillo
- Universidad de Málaga
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- Andrea Zisman
- The Open University
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Description
<jats:p>Despite considerable research efforts on handling uncertainty in self-adaptive systems, a comprehensive understanding of the precise nature of uncertainty is still lacking. This paper summarises the findings of the 2023 Bertinoro Seminar on Uncertainty in Self- Adaptive Systems, which aimed at thoroughly investigating the notion of uncertainty, and outlining open challenges associated with its handling in self-adaptive systems. The seminar discussions were centered around five core topics: (1) agile end-toend handling of uncertainties in goal-oriented self-adaptive systems, (2) managing uncertainty risks for self-adaptive systems, (3) uncertainty propagation and interaction, (4) uncertainty in self-adaptive machine learning systems, and (5) human empowerment under uncertainty. Building on the insights from these discussions, we propose a research agenda listing key open challenges, and a possible way forward for addressing them in the coming years.</jats:p>
Journal
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- ACM SIGSOFT Software Engineering Notes
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ACM SIGSOFT Software Engineering Notes 48 (4), 20-36, 2023-10-13
Association for Computing Machinery (ACM)
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Keywords
Details 詳細情報について
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- CRID
- 1360302864803909248
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- HANDLE
- 10446/262957
- 2108/349044
- 11311/1259378
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- ISSN
- 01635948
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- Article Type
- journal article
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- Data Source
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- Crossref
- KAKEN
- OpenAIRE