Mathematical Methods Applied in Artificial Intelligence and Multi-Agent Systems

• Format: eBook
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2024
• Subjects: adaptive dynamic programming; adaptive law; automatic curriculum learning; bias parameter; bilingual-visual harmony; clustered multi-agent systems; common target; communication delay; congestion; consensus; containment control; curiosity; deep reinforcement learning; distributed control; disturbance observer; event-triggered control; homogeneous; LFT; LMI; Mathematics and Science; mixed-delay-dependent functional; model identification; moving-horizon control; multi-agent system; multi-agent systems; multi-modal neural machine translation; neutral-type neural networks; opinion dynamics; optimal control; output feedback; polarization; Reference, Information and Interdisciplinary subjects; reinforcement learning; Research and information: general; robotic swarm; robust ℋ∞ control; sampled-data control; sparse reward; swarm intelligence; synchronization problem; throughput; time delay; traffic control; two-DOF FJMS; visual annotation; white noise; wide-area network
• ISBN: 9783725818969; 3725818959; 3725818967; 9783725818952
• DOI: 10.3390/books978-3-7258-1896-9

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.