An agent composition framework for the J-Park simulator - a knowledge graph for the process industry

• Main Authors: Zhou, Xiaochi, Eibeck, Andreas, Lim, Mei Qi, Krdzavac, Nenad B., Kraft, Markus
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Chemical engineering; Semantic Web; Semantic Web Service Composition
• Online Access: https://hdl.handle.net/10356/152235
• Institution: Nanyang Technological University

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.