Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems
Due to rapid developments in computing, communication, and sensing technology, multi-agent systems have become increasingly ubiquitous. Their applications include mobile sensor networks, autonomous vehicles, intelligent transportation systems, and smart grids. The complex unknown environment and ina...
Zapisane w:
| Format: | Online |
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| Język: | angielski |
| Wydane: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Hasła przedmiotowe: | |
| Dostęp online: | ONIX_20250220_9783725818952_42 |
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| _version_ | 1869517152738869248 |
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| collection | Directory of Open Access Books |
| description | Due to rapid developments in computing, communication, and sensing technology, multi-agent systems have become increasingly ubiquitous. Their applications include mobile sensor networks, autonomous vehicles, intelligent transportation systems, and smart grids. The complex unknown environment and inaccurate dynamics prose additional challenges for the modeling, control, and optimization of such systems. Therefore, data science and machine learning are providing opportunities to develop artificial intelligence-based methods and enable new control and optimization paradigms for multi-agent systems. The aim of this Special Issue is to bring together significant developments in the interface between machine learning, neurodynamics, and swarm intelligence. |
| format | Online |
| id | doab-20.500.12854ir-152678 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1526782025-02-20T12:53:55Z Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems Hu, Jiangping Peng, Zhinan robotic swarm common target throughput congestion traffic control deep reinforcement learning automatic curriculum learning curiosity sparse reward neutral-type neural networks synchronization problem mixed-delay-dependent functional sampled-data control communication delay model identification optimal control multi-agent systems adaptive dynamic programming reinforcement learning opinion dynamics bias parameter homogeneous polarization consensus event-triggered control disturbance observer containment control output feedback time delay multi-agent system adaptive law white noise two-DOF FJMS LFT LMI moving-horizon control robust ℋ∞ control wide-area network clustered multi-agent systems distributed control swarm intelligence multi-modal neural machine translation bilingual-visual harmony visual annotation thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science Due to rapid developments in computing, communication, and sensing technology, multi-agent systems have become increasingly ubiquitous. Their applications include mobile sensor networks, autonomous vehicles, intelligent transportation systems, and smart grids. The complex unknown environment and inaccurate dynamics prose additional challenges for the modeling, control, and optimization of such systems. Therefore, data science and machine learning are providing opportunities to develop artificial intelligence-based methods and enable new control and optimization paradigms for multi-agent systems. The aim of this Special Issue is to bring together significant developments in the interface between machine learning, neurodynamics, and swarm intelligence. 2025-02-20T12:53:53Z 2025-02-20T12:53:53Z 2024 book ONIX_20250220_9783725818952_42 9783725818952 9783725818969 https://directory.doabooks.org/handle/20.500.12854/152678 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/9876 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1896-9 10.3390/books978-3-7258-1896-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725818952 9783725818969 224 Basel open access |
| spellingShingle | robotic swarm common target throughput congestion traffic control deep reinforcement learning automatic curriculum learning curiosity sparse reward neutral-type neural networks synchronization problem mixed-delay-dependent functional sampled-data control communication delay model identification optimal control multi-agent systems adaptive dynamic programming reinforcement learning opinion dynamics bias parameter homogeneous polarization consensus event-triggered control disturbance observer containment control output feedback time delay multi-agent system adaptive law white noise two-DOF FJMS LFT LMI moving-horizon control robust ℋ∞ control wide-area network clustered multi-agent systems distributed control swarm intelligence multi-modal neural machine translation bilingual-visual harmony visual annotation thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title | Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title_full | Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title_fullStr | Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title_full_unstemmed | Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title_short | Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems |
| title_sort | mathematical methods applied in artificial intelligence and multi agent systems |
| topic | robotic swarm common target throughput congestion traffic control deep reinforcement learning automatic curriculum learning curiosity sparse reward neutral-type neural networks synchronization problem mixed-delay-dependent functional sampled-data control communication delay model identification optimal control multi-agent systems adaptive dynamic programming reinforcement learning opinion dynamics bias parameter homogeneous polarization consensus event-triggered control disturbance observer containment control output feedback time delay multi-agent system adaptive law white noise two-DOF FJMS LFT LMI moving-horizon control robust ℋ∞ control wide-area network clustered multi-agent systems distributed control swarm intelligence multi-modal neural machine translation bilingual-visual harmony visual annotation thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| topic_facet | robotic swarm common target throughput congestion traffic control deep reinforcement learning automatic curriculum learning curiosity sparse reward neutral-type neural networks synchronization problem mixed-delay-dependent functional sampled-data control communication delay model identification optimal control multi-agent systems adaptive dynamic programming reinforcement learning opinion dynamics bias parameter homogeneous polarization consensus event-triggered control disturbance observer containment control output feedback time delay multi-agent system adaptive law white noise two-DOF FJMS LFT LMI moving-horizon control robust ℋ∞ control wide-area network clustered multi-agent systems distributed control swarm intelligence multi-modal neural machine translation bilingual-visual harmony visual annotation thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| url | ONIX_20250220_9783725818952_42 |