Balancing Gains, Risks, Costs, and Real-Time Constraints in the Ball Passing Algorithm for the Robotic Soccer

摘要

We are looking for a generic solution for the optimized ball passing problem in the robotic soccer which is applicable to many digital simulated sports games with ball. In doing so, we show that previously published ball passing methods do not properly address the necessary balance between the anticipated rewards, costs, and risks. The multi-criteria nature of this optimization problem requires using the Pareto optimality approach. We propose a scalable and robust solution for decision making, as its quality degrades in a graceful way once the real time constrains are kicking in.