Multi Agent

This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. This book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems.

This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Workshop on Engineering Multi-Agent Systems, EMAS 2020, held in Auckland, New Zealand, in May 2020. Due to COVID-19 pandemic the conference was held virtually.

This book contains three well-written research tutorials that inform the graduate reader about the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends.