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首页> 外文会议>IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion >A Cognitive Control System for Managing Runtime Uncertainty in Self-Integrating Autonomic Systems
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A Cognitive Control System for Managing Runtime Uncertainty in Self-Integrating Autonomic Systems

机译：自集成自主系统中用于管理运行时不确定性的认知控制系统

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摘要

Autonomic systems manage resources to achieve high-level goals with minimum human intervention, by continuously adapting based on a model of themselves and of their environment. Adaptation requires managing runtime uncertainties produced by changes within a dynamic environment, by modeling unexpected situations that were not considered at design time. This challenge becomes even more critical in a self-integration context where autonomic systems, traditionally engineered systems, and human organizations, influence each other in a shared environment. In this paper, we propose a cognitive control system that aims to manage runtime uncertainty in self-integrating autonomic systems. The cognitive control system autonomously extends the existing modeling language, by generating knowledge to represent unexpected situations as they are encountered at runtime, and reasons on the resulting model, in order to determine the required adaptation knowledge. As proof-of-concept validation, we present a scenario supported by an implementation of our proposal, illustrating the capabilities of the cognitive control system in the smart home domain. The obtained results set the basis for further studying the modeling language for describing the adaptation knowledge, with the objective of enriching the collaboration capabilities of autonomic systems in a self-integration context as future work.
机译：自主系统通过根据自身和环境模型进行持续调整，以最少的人工干预来管理资源，以实现高层目标。适应需要通过对动态环境中的更改所产生的运行时不确定性进行管理，方法是对设计时未考虑的意外情况进行建模。在自主系统，传统工程系统和人类组织在共享环境中相互影响的自我整合环境中，这一挑战变得更加关键。在本文中，我们提出了一种认知控制系统，旨在管理自集成自主系统中的运行时不确定性。认知控制系统通过生成知识以表示运行时遇到的意外情况以及生成模型的原因来自主扩展现有的建模语言，从而确定所需的适应性知识。作为概念验证，我们提出了一个由提案实施支持的方案，说明了智能家居领域中认知控制系统的功能。获得的结果为进一步研究用于描述适应性知识的建模语言奠定了基础，其目的是丰富自主系统中自主系统的协作能力，作为未来的工作。

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