Playmaker: Graphical definition of formations and setplays

The fall of chess as a main domain for Artificial Intelligence (AI) research, after the victory of Deep Blue over Kasparov, put forward robotic soccer as a new challenging domain for AI researchers. Robotic Soccer is very appropriate for researching in Distributed AI problems, e.g. coordination methodologies, whose results can later be applied to other domains. Coordination can be defined as the capability of several agents to work together as a team, in order to accomplish a common goal. In the context of robotic soccer, several aspects may benefit from appropriate coordination methodologies, since team play is decisive for winning the games. This paper presents a methodology to enable a team of robotic soccer agents to coordinate their positioning in the field, and a methodology that enables them to cooperatively execute predefined set plays (flexible plans). Both coordination methods are used in real soccer and sports in general, commonly known as formations and set plays respectively. However, its use in a team of autonomous agents is still unexplored and is a major innovation of this work. A graphical tool to define formations and set plays was fully developed in the context of this work offering a quicker and more appealing way to define both formations and set plays. The tool's interface was inspired on ”blackboard” applications, used nowadays for the same purpose in real sports. The tool enables very easy definition of set plays that may then be executed in real-time during the matches. Examples of complete set plays and their practical execution are also described, showing the usefulness of the set play concept and the utility of the developed tool.