The role of n in the n-mates evaluation method: a quantitative analysis

The evolution of controllers for heterogeneous Multi-Agent Systems, wherein two or more agents interact, is a fascinat- ing area of research. While using evolutionary algorithms is a straightforward approach, the resulting behavior strongly de- pends 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 prob- lems (i.e., foraging, escaping, aggregation). Statistical analy- sis demonstrates that selecting n = 5 results in superior out- comes across all investigated parameters (n ∈ [1, 2, 5, 10]).