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Title: An agent composition framework for the J-Park simulator - a knowledge graph for the process industry
Authors: Zhou, Xiaochi
Eibeck, Andreas
Lim, Mei Qi
Krdzavac, Nenad B.
Kraft, Markus
Keywords: Engineering::Chemical engineering
Issue Date: 2019
Source: Zhou, X., Eibeck, A., Lim, M. Q., Krdzavac, N. B. & Kraft, M. (2019). An agent composition framework for the J-Park simulator - a knowledge graph for the process industry. Computers and Chemical Engineering, 130, 106577-.
Journal: Computers and Chemical Engineering
Abstract: Digital twins, Industry 4.0 and Industrial Internet of Things are becoming ever more important in the process industry. The Semantic Web, linked data, knowledge graphs and web services/agents are key technologies for implementing the above concepts. In this paper, we present a comprehensive semantic agent composition framework. It enables automatic agent discovery and composition to generate cross-domain applications. This framework is based on a light-weight agent ontology, OntoAgent, which is an adaptation of the Minimal Service Model (MSM) ontology. The MSM ontology was extended with grounding components to support the execution of an agent while keeping the compatibility with other existing web service description standards and extensibility. We illustrate how the comprehensive agent composition framework can be integrated into the J-Park Simulator (JPS) knowledge graph, for the automatic creation of a composite agent that simulates the dispersion of the emissions of a power plant within a selected spatial area.
ISSN: 0098-1354
DOI: 10.1016/j.compchemeng.2019.106577
Rights: © 2019 Elsevier Ltd. All rights reserved. This paper was published in Computers and Chemical Engineering and is made available with permission of Elsevier Ltd.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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