Integrating Model-Driven Engineering as the Next Challenge for Artificial Intelligence – Application to Risk and Crisis Management

F. Bénaben, M. Lauras, Audrey Fertier, Nicolas Salatgé
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引用次数: 3

Abstract

Artificial Intelligence (AI) is currently on top of the hype regarding simultaneously research publications and industrial development. However, the current status of AI makes it quite far and different from the current understanding of Human intelligence. One suggestion that is made in this article is that Model-Driven approaches could be considered as an interesting avenue to complement classical visions of AI and to provide some missing features. Specifically, the use of Model-Driven Engineering tools (such as metamodel and model transformation) could benefit to the domain of AI by introducing a way to extend the apprehension of unknown situations. To support that proposal, an illustrative example is provided regarding the domain of risk and crisis management.
集成模型驱动工程作为人工智能的下一个挑战——在风险和危机管理中的应用
目前,人工智能(AI)在研究出版物和产业发展的炒作中处于领先地位。然而,人工智能的现状使其与目前对人类智能的理解相差甚远。本文提出的一个建议是,模型驱动方法可以被视为一种有趣的途径,以补充人工智能的经典愿景,并提供一些缺失的功能。具体地说,模型驱动工程工具(如元模型和模型转换)的使用可以通过引入一种扩展对未知情况的理解的方法而有益于人工智能领域。为了支持这一建议,提供了一个关于风险和危机管理领域的说明性示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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