Multiagent System Technologies

The papers cover a broad area of topics of interest ranging from issues of agent-based coordination to simulation to negotiation.

This book discuss multi-agent technologies (MATs) and machine learning (ML). These tools can be integrated and applied in industry, commerce, energy, medicine, psychology, and other areas.

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 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.

PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems.