对自适应系统中不确定性的理解和管理的研究议程

Danny Weyns, Radu Calinescu, Raffaela Mirandola, Kenji Tei, Maribel Acosta, Amel Bennaceur, Nicolas Boltz, Tomas Bures, Javier Camara, Ada Diaconescu, Gregor Engels, Simos Gerasimou, Ilias Gerostathopoulos, Sinem Getir Yaman, Vincenzo Grassi, Sebastian Hahner, Emmanuel Letier, Marin Litoiu, Lina Marsso, Angelika Musil, Juergen Musil, Genaina Nunes Rodrigues, Diego Perez-Palacin, Federico Quin, Patrizia Scandurra, Antonio Vallecillo, Andrea Zisman
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引用次数: 0

摘要

尽管在处理自适应系统中的不确定性方面进行了大量的研究,但对不确定性的精确性质仍然缺乏全面的理解。本文总结了2023年Bertinoro自适应系统不确定性研讨会的研究结果,该研讨会旨在彻底研究不确定性的概念,并概述了与自适应系统处理不确定性相关的公开挑战。研讨会围绕五个核心主题展开讨论:(1)面向目标的自适应系统中不确定性的敏捷端到端处理;(2)自适应系统的不确定性风险管理;(3)不确定性传播与交互;(4)自适应机器学习系统中的不确定性;(5)不确定性下的人类赋权。基于这些讨论的见解,我们提出了一个研究议程,列出了关键的开放挑战,以及未来几年解决这些挑战的可能方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a Research Agenda for Understanding and ManagingUncertainty in Self-Adaptive Systems
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.
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