The evolution of controllers for heterogeneous Multi-Agent Systems, wherein two or more agents interact, is a fascinating area of research. While using evolutionary algorithms is a straightforward approach, the resulting behavior strongly depends on the capabilities of each individual and the type of established interaction. Recently, a novel technique, called n-mates evaluation, has been proposed to better estimate the contribution of individuals and generate more adaptive agents. However, the significance of parameter n has not been investigated. In this work, we analyze the impact of the parameter on the performance and adaptability of two agents collaborating to solve various evolutionary benchmark problems (i.e., foraging, escaping, aggregation). Statistical analysis demonstrates that selecting n = 5 results in superior outcomes across all investigated parameters ( n ∈ [1, 2, 5, 10]).