The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Smart Agents in Industrial Cyber–Physical Systems
Open accessAbstract
Future industrial systems can be realized using the cyber-physical systems (CPSs) that advocate the coexistence of cyber and physical counterparts in a network structure to perform the system's functions in a collaborative manner. Multiagent systems share common ground with CPSs and can empower them with a multitude of capabilities in their efforts to achieve complexity management, decentralization, intelligence, modularity, flexibility, robustness, adaptation, and responsiveness. This work surveys and analyzes the current state of the industrial application of agent technology in CPSs, and provides a vision on the way agents can effectively enable emerging CPS challenges.
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Cites
Cyber-physical Production Systems: Roots, Expectations and R&D Challenges
Monostori, L. (2014) · Procedia CIRP · doi:10.1016/j.procir.2014.03.115 · Cited by 1,215
Agent-based distributed manufacturing control: A state-of-the-art survey
Leitão, P. (2009) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2008.09.005 · Cited by 841
Multi-agent systems in a distributed smart grid: Design and implementation
Pipattanasomporn, M., Feroze, H., & Rahman, S. (2009) · 2009 IEEE/PES Power Systems Conference and Exposition · doi:10.1109/psce.2009.4840087 · Cited by 718
Mahnke, W., Leitner, S.-H., & Damm, M. (2009) · Springer eBooks · doi:10.1007/978-3-540-68899-0 · Cited by 715
Agent-Based Systems for Manufacturing
Monostori, L., Váncza, J., & Kumara, S. R. T. (2006) · CIRP Annals · doi:10.1016/j.cirp.2006.10.004 · Cited by 689
Leitão, P., Colombo, A. W., & Karnouskos, S. (2016) · Computers in Industry · doi:10.1016/j.compind.2015.08.004 · Cited by 672
Self-citationA Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems
Strasser, T., Andren, F., Kathan, J., Cecati, C., Buccella, C., Siano, P., Leitao, P., Zhabelova, G., Vyatkin, V., Vrba, P., et al. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2361486 · Cited by 572
Self-citationSwarm intelligence. A whole new way to think about business.
Bonabeau, E. W., & Meyer, C. (2001) · PubMed · Cited by 394
IEC 61499 as Enabler of Distributed and Intelligent Automation: State-of-the-Art Review
Vyatkin, V. (2011) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2011.2166785 · Cited by 362
Djurdjanovic, D., Lee, J., & Ni, J. (2003) · Advanced Engineering Informatics · doi:10.1016/j.aei.2004.07.005 · Cited by 305
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Cited by
Industrial artificial intelligence for industry 4.0-based manufacturing systems
Lee, J., Davari, H., Singh, J., & Pandhare, V. (2018) · Manufacturing Letters · doi:10.1016/j.mfglet.2018.09.002 · Cited by 870
Self-citationHossain, E., Khan, I., Un-Noor, F., Sikander, S. S., & Sunny, M. S. H. (2019) · IEEE Access · doi:10.1109/access.2019.2894819 · Cited by 513
Cybersecurity of industrial cyber-physical systems: A review
Kayan, H., Nunes, M., Rana, O., Burnap, P., & Perera, C. (2022) · ACM Computing Surveys · doi:10.1145/3510410 · Cited by 261
System architectures for Industrie 4.0 applications: Derivation of a generic architecture proposal
Trunzer, E., Calà, A., Leitão, P., Gepp, M., Kinghorst, J., Lüder, A., Schauerte, H., Reifferscheid, M., & Vogel-Heuser, B. (2019) · Production Engineering · doi:10.1007/s11740-019-00902-6 · Cited by 103
Insider threat detection in cyber-physical systems: a systematic literature review
Al-Mhiqani, M. N., Alsboui, T., Al-Shehari, T., Abdulkareem, K. H., Ahmad, R., & Mohammed, M. A. (2024) · Computers and Electrical Engineering · doi:10.1016/j.compeleceng.2024.109489 · Cited by 53
Metadata
- Authors
- Leitao, P., Karnouskos, S., Ribeiro, L., Lee, J., Strasser, T., & Colombo, A. W.
- Venue
- Proceedings of the IEEE
- Published
- 2016-05
- Volume
- 104
- Issue
- 5
- Pages
- 1086-1101
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W2325775534
- Cited by
- 462
- References
- 38
- FWCI
- 70.73
- Type
- journal article
- Language
- en
- Open access
- green
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- Leitao, P., Karnouskos, S., Ribeiro, L., Lee, J., Strasser, T., & Colombo, A. W. (2016). Smart Agents in Industrial Cyber–Physical Systems. Proceedings of the IEEE. https://doi.org/10.1109/jproc.2016.2521931
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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