Predrag S. Stanimirović - Böcker

This book presents the proceedings of the 6th EAI International Conference on Robotics and Networks 2022 (ROSENET 2022). The conference explores the integration of networks and robotic technologies, which has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. The authors posit that big networks will be the main approach to the next generation of robotic research, with the explosive number of networks models and increasing computational power of computers significantly extending the number of potential applications for robotic technologies while also bringing new challenges to the networking community. The conference provided a platform for researchers to share up-to-date scientific achievements in this field. The conference took place at Swansea University, Wales, Great Britain.

The authors posit that big networks will be the main approach to the next generation of robotic research, with the explosive number of networks models and increasing computational power of computers significantly extending the number of potential applications for robotic technologies while also bringing new challenges to the networking community.

Delivering innovative methods for addressing complex systems, this book presents the latest advances in hybrid modeling, machine learning, and digital technologies. Based on selected papers from the III International Workshop “Hybrid Methods of Modeling and Optimization in Complex Systems” held December 2–4, 2024, in Krasnoyarsk, Russia, the book covers hybrid modeling and optimization, intelligent data analysis, financial forecasting, industrial and educational digitalization, AI-guided decision support, and digital system security. Readers will find such interdisciplinary applications as climate project modeling, agricultural digital services, and the digital platform economy; e-learning analysis and digital competence development; digital twins and production optimization; as well as research on network systems. It is essential for researchers, practitioners, and educators seeking practical solutions and advanced hybrid methods for diverse scientific and engineering challenges.

mso-fareast-theme-font: minor-latin;">Based on the authors’ research that has been published in leading scientific journals, the book spans a variety of disciplines, including linear and multilinear algebra, generalized inverses, recurrent neural networks, dynamical systems, time-varying problem solving, and unconstrained nonlinear optimization.

This volume presents selected papers from the IV International Workshop on Hybrid Methods of Modeling and Optimization in Complex Systems, introducing hybrid methodologies integrating mathematical modeling, machine learning, and intelligent optimization to enhance prediction, analysis, and decision-making. The volume covers hybrid modeling and optimization, AI-driven monitoring systems, cybersecurity and data protection, blockchain infrastructures, logistics and manufacturing integration, as well as advances in data mining, recommender systems, reinforcement learning, pattern recognition, and adaptive intelligence using evolutionary algorithms and neural networks. Combining theoretical advances with applied case studies, the book demonstrates how hybrid methods improve predictive accuracy, system efficiency, and intelligent decision support. It is intended for researchers, engineers, data scientists, and graduate students working with complex systems and artificial intelligence.