An agent composition framework for the J-Park Simulator - A knowledge graph for the process industry
- The light-weight ontology, OntoAgent, has been developed based on MSM ontology.
- An agent composition framework based on OntoAgent has been developed.
- A cross-domain air pollution scenario is used to illustrate the agent composition framework.
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.
- This paper draws from preprint 227: An agent composition framework for the J-Park Simulator - a knowledge graph for the process industry
- Access the article at the publisher: DOI: 10.1016/j.compchemeng.2019.106577
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