The scientific theme of the book is “Sustainability for the digital manufacturing era” which is focused on how the technological enablers of digital systems drive the sustainability for products, processes, manufacturing, and logistics systems in the industry of the future. The book’s chapters describe sustainability drivers specific to the technological advances that motivate, encourage, and engage the economic, social, and environmental aspects within intelligent manufacturing and logistics systems. The novelty of this approach consists in extending the economic sustainability of digital manufacturing with the ethical perspective at human social scale. The general scope of the book is to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods, and solutions for the digital transformation of manufacturing through service orientation in holonic and agent-based control with distributed intelligence. The book’s readership is comprised of researchers and engineers working in the value chain of products and processes, who develop digital control solutions in the “Industry of the Future” vision. The book is also addressed to master’s and Ph.D. students enrolled in Engineering Sciences programs.

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

This book describes the implementation of autonomous control with multiagent technology. Therewith, it tackles the challenges of supply network management caused by the complexity, the dynamics, and the distribution of logistics processes. The paradigm of autonomous logistics reduces the computational complexity and copes with the dynamics locally by delegating process control to the participating objects. As an example, shipping containers may themselves plan and schedule their way through logistics networks in accordance with objectives imposed by their owners. The technologies enabling autonomous logistics are thoroughly described and reviewed. The presented solution has been used in a realistic simulation of real-world container logistics processes. The validation shows that autonomous control is feasible and that it outperforms the previous centralised dispatching approach by significantly increasing the resource utilisation efficiency. Moreover, the multiagent system relieves human dispatchers from dealing with standard cases, giving them more time to solve exceptional cases appropriately.

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

This book constitutes the 16th edition of the annual Multi-Agent Programming Contest, MAPC 2022.
It gives an overview of the competition, describes the current scenario. The first paper describes the contest in general and this edition in particular, focusing on the organizers’ observations. The following papers are written by the participants of the contest, describing their team of agents and its performance in more detail.

This book describes an effective approach to the cooperative and coordinated control of multivehicle systems. This rigorous analytic approach guarantees the stability of coordinated and cooperating vehicles using distributed protocols and uses low-energy, event-triggered mechanisms for networked vehicle control. The text covers:

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

This book constitutes the proceedings of the 19th Russian Conference on Artificial Intelligence, RCAI 2021, held in Moscow, Russia, in October 2021.