This paper introduces a novel approach for enhancing the performance of soccer robots through the implementation of an artificial immune network-based action selection mechanism. Inspired by the principles of the human immune system, the proposed mechanism leverages artificial immune networks to facilitate intelligent decision-making in dynamic soccer environments. By modeling the interaction between robots and their surroundings as an immune response process, the system adapts its actions based on perceived stimuli and previous experiences. Through simulations and experimental validation, we demonstrate the effectiveness of the proposed approach in improving the decision-making capabilities and overall performance of soccer robots in competitive scenarios.