人工智能企业信息系统

IF 4.4 4区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Milan Zdravković, H. Panetto
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引用次数: 0

摘要

第四次工业革命标志着简单和重复的人工任务的工业自动化时代的结束。然后,它为具有明确目标的模仿人类智能的努力开辟了一个新的舞台。这个领域促进了i)机器驱动的决策,ii)使用人类易于表达和理解的形式进行无缝的机器对机器通信,iii)解决由不确定和未知变量驱动的问题,以及iv)其他需要更复杂的考虑和行动的活动,这些活动在过去通常由人类实施。随着人工智能(AI)的发展,企业信息系统(EIS)越来越有能力基于获得的理解来感知和感知(甚至超越人类的认知范围)、分析或理解和响应。这种组合是通过使用大数据、显著改进的算法和足够的计算能力来训练和运行大量数据的算法而成为可能的。在本期特刊中,介绍了人工智能环境信息系统实现的概念(zdravkovovic, Panetto, and Weichhart 2021),以提供一种新的思维方式,架构,设计,开发和使用环境信息系统。它被放在广泛讨论的数据支持的顶部,有时在所谓的传感企业的背景下。该企业利用传感器、嵌入式电子和多智能体系统等技术不断地监听其内部和外部环境。尽管今天对人工智能的炒作是由复杂深度学习架构和模型的性能驱动的,但符号和非符号人工智能应用被认为反映了基于逻辑和基于数据的方法的挑战和机遇的同等重要性。特刊在出版商的网站和电子邮件上做了广告。此外,在第8届信息社会与技术国际会议(ICIST 2018)上组织的题为“智能与传感系统的(工业)互联网-物联网”的特别会议上选出的论文的作者被邀请将这些论文的扩展版本提交给特刊。已收到20份投稿,经过几轮审查和修订,6份手稿被接受出版。这些手稿将在下一节中简要介绍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence-enabled enterprise information systems
The fourth industrial revolution has marked the end of the industrial automation era of simple and repetitive human tasks. Then, it opened a new arena for the efforts of mimicking human intelligence with a clear objective. This arena facilitates i) machinedriven decision-making, ii) seamless machine-to-machine communication using the formalisms easily expressed and understood by humans, iii) solving problems driven by uncertain and unknown variables, and iv) other activities that require more complex considerations and actions, in which humans typically implement in the past. With Artificial Intelligence (AI), Enterprise Information Systems (EIS) are becoming increasingly capable of sensing and perceive (even reach beyond the human cognitive horizon), analyse, or understand and respond, based on the acquired understanding. This combination was made possible using big data, significantly improved algorithms and sufficient computational power to train and run those algorithms with vast amounts of data. In this Special Issue, the concept of AI EIS enablement (Zdravković, Panetto, and Weichhart 2021) is introduced to provide the umbrella for a new way of thinking, architecting, designing, developing and using the EIS. It is placed on the top of the widely discussed data-enablement, sometimes in the context of so-called sensing enterprise. This enterprise continuously listens to its internal and external environments using the technologies, such as sensors, embedded electronics and multi-agent systems. Although today’s hype on AI is driven by the performance of complex deep learning architectures and models, both symbolic and non-symbolic AI applications were considered to reflect the equal importance of challenges and opportunities for logic-based and data-based methods. The Special Issue was advertised on the website of the publisher and by email. Also, the authors of the selected papers from the special session with the title ‘(Industrial) Internetof-Things for Smart & Sensing Systems’, organised at the 8th International Conference for Information Society and Technology (ICIST 2018) were invited to submit the extended versions of those papers to the Special Issue. Twenty submissions have been received, and after several rounds of reviews and revisions, six manuscripts were accepted for publication. Those manuscripts are shortly presented in the following section.
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来源期刊
Enterprise Information Systems
Enterprise Information Systems 工程技术-计算机:信息系统
CiteScore
11.00
自引率
6.80%
发文量
24
审稿时长
6 months
期刊介绍: Enterprise Information Systems (EIS) focusses on both the technical and applications aspects of EIS technology, and the complex and cross-disciplinary problems of enterprise integration that arise in integrating extended enterprises in a contemporary global supply chain environment. Techniques developed in mathematical science, computer science, manufacturing engineering, and operations management used in the design or operation of EIS will also be considered.
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