Intelligent decision making in multi-agent robot soccer system through compounded artificial neural networks

This paper proposes a two-stage approach using artificial neural networks for the intelligent decision-making by the robots in a MiroSot small league. The first stage involves the use of an evolutionary algorithm for getting a rough estimate of the neural network weight matrices. The proposed approach is then generalized to the case of quick, intelligent and accurate decision-making in the case of a robot soccer system with robots utilizing the concept of compounded artificial neural networks. In the proposed approach a soccer field is divided into three zones so that the decision of the robots depends on the zone of the ball at any instant. The concept of a forward robot is also introduced in this paper to enhance the accuracy of the decision-making with the global strategy of advancing towards the goal area of the opponent for scoring a goal. Simulation results indicate that the proposed techniques are very effective in taking intelligent decision-making in a multi-agent robot soccer system in MiroSot small league as well as middle league.