This is an interesting book published as a version of a PhD thesis. It focuses on the analytics of fundamental aspects of swarm robots modeled as multiagent systems, where individual and collective behaviors of the swarms play key roles in the success of the systems.

Both relevant computing fields of swarm intelligence and multiagent systems have matured to some extent and have been successfully used in various areas of modeling and problem solving across a vast horizon of domains. Recently, particular interest has been growing in the area of teams of small-scale robots, especially groups of unmanned aerial vehicles (UAVs), which are also known as robotic swarms. The main issue with multiagent systems in general, and swarm robotics in particular, is how to handle group decision-making and how to achieve successful collective behaviors within the given circumstances. It requires consensus among the individuals, where each relies on its own experiences and individual skills. This book nicely approaches these issues and analyzes the fundamental theory behind the formation, consensus, and containment control of the behaviors. It particularly focuses on higher-order linear systems rather than first- or second-order ones, and considers the problems as time-variant problems, which helps in analyzing the long-term behaviors of designed systems.

Although a number of examples are provided, I might have given examples of more well-known swarm algorithms and demonstrated how the theory produced can be implemented for these specific algorithms so that readers, especially those new to the field, can maximally benefit.