ARCHON: a distributed artificial intelligence system for industrial application
Foundations of distributed artificial intelligence
Agents for complex control systems
Automation, control and complexity
An agent-based approach for building complex software systems
Communications of the ACM
Information agent technology for the Internet: a survey
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Rationales for Holonic Applications in Chemical Process Industries
Proceedings of the 9th ECCAI-ACAI/EASSS 2001, AEMAS 2001, HoloMAS 2001 on Multi-Agent-Systems and Applications II-Selected Revised Papers
Industrial MAS for Planning and Control
Proceedings of the 9th ECCAI-ACAI/EASSS 2001, AEMAS 2001, HoloMAS 2001 on Multi-Agent-Systems and Applications II-Selected Revised Papers
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Scalable Semantic Brokering over Dynamic Heterogeneous Data Sources in InfoSleuth"
IEEE Transactions on Knowledge and Data Engineering
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
A Multi-Agent System Based Approach to Intelligent Process Automation Systems
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
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An approach to combine information access and control operations in a process automation system extended with multi-agent system technology is presented in this paper. According to this approach a multi-agent system supervises an ordinary process automation system by performing higher-level information access and control operations. The information access operations are aimed for actively combining information from different sources depending on the monitoring tasks of the users. The control operations of the multi-agent system are supervisory control tasks performed either in sequential or iterative fashion. The expected benefit of the multi-agent system is enhanced adaptability of the automation system and increased situation awareness of its users. The architecture of the multi-agent system is based on the BDI agent model and utilization of so-called ontologies. An approach for engineering applications for this kind of a multi-agent system is also discussed. The approach is demonstrated with results from experiments performed with industrial test data and a laboratory test process.