Recent robotics advancements are making it possible to deploy large numbers of low-cost robots for tasks like surveillance and search. However, coordinating a group of robots to perform these kinds of tasks is still difficult. Recent research papers on multi-robot systems are summarised in this report. It's divided into two sections. The first section covered research into the pattern formation problem; specifically, how robots can be commanded to form a pattern and keep it. The second section examines the research into adaptive strategies for managing networks of robots. In particular, we've looked into (1) how evolution is used to generate group behaviours, and (2) how learning (lifelong adaptation) is used to make multi-robot systems respond to changes in the environment and in the capabilities of individual robots.