Approaching a Formal Soccer Theory from Behaviour Specifications in Robotic Soccer

This chapter discusses a top-down approach to modelling soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple robotic soccer leagues in the RoboCup. We investigate if and how soccer theory can be formalised such that specification and execution is possible. The advantage is clear: theory abstracts from hardware and from specific situations in different leagues. We introduce basic primitives compliant with the terminology known in soccer theory, discuss an example on an abstract level and formalise it. The formalisation of soccer presented here is appealing. It goes beyond the behaviour specification of soccer playing robots. For sports science a unified formal soccer theory might help to better understand and to formulate basic concepts in soccer. The possibility of the formalisation to develop computer programs which allow to simulate and to reason about soccer moves might also take sports science a step further. This research has been carried out within the special research program DFG-SPP 1125 Cooperative Teams of Mobile Robots in Dynamic Environments and the Transregional Collaborative Research Center SFB/TR 8 on Spatial Cognition. Both research programs are funded by the German Research Foundation (DFG). A short and preliminary predecessor of this paper appeared as [1]. 1 Robotics and Soccer In 1997, the first RoboCup, the international world championship in robotic soccer was held. The event was part of the International Joint Conference on Artificial Intelligence (IJCAI), and set a new benchmark: the goal of RoboCup is to foster Artificial Intelligence (AI) and robotics research so that by 2050 a team of autonomous humanoid robots can be built that will be able to win against the human soccer world champion [2]. Similar to the goal of beating the human world champion in chess with a computer, in RoboCup the journey is the reward. The initiators of RoboCup have chosen soccer as a testbed and common research platform because it covers a wide range of problems from robotics to AI: from energy supply, creating robust robots, over vision and sensor fusion to coordination, cooperative multiagent systems, behaviour programming, machine learning, and strategy acquisition, and many more issues have to be solved until it will be possible to reach this goal. Soccer is an interesting research problem because it is a multiagent domain where agents have to cooperate with their team-mates and deal with adversarial agents in real-time simultaneously. Moreover, during the first years of research in robotic soccer it has already turned out that soccer playing robots can also be interesting by themselves, because matches between robots or computer programs can be quite entertaining and exciting – not only for the developers of the respective teams.