The field of robot soccer provides numerous opportunities for the application of AI methods for game strategy development. Robot soccer is a part of standard applications of distributed system control in real time. The software part of a distributed control system is realized by decision making and executive agents. The algorithm of agents' cooperation was proposed with the control agent on a higher level. The algorithms for agents realized in robots are the same. Real-time dynamic simple strategy description and strategy learning possibility based on game observation is important for discovering opponent's strategies and searching for tactical group movements, simulation and synthesis of suitable counter-strategies. For the improvement of game strategy, we are developing an abstract description of the game and propose ways to use this description (e.g. for learning rules and adapting team strategies to every single opponent).