The artificial entities dwell in a homogeneous world and are completely identical at the start of the simulation. They are gregarious and perform dominance interactions in which the effects of winning and losing are self-reinforcing. Varying essential parameters of the model revealed that: 1) Social-spatial patterns are stronger among entities that perceive each others rank directly compared to those that estimate rank of others based on personal experiences. 2) Stronger social-spatial patterns result when entities obligatory attack others than when attack-rate was negatively dependent on rank-distance. 3) Raising the intensity of attack increased the centrality of dominants for the Obligatory attack system, but weakened it for the Rank-Distance Decreasing attack system. Also, other social interaction patterns emerged, such as bidirectionality of aggression and a correlation between rank and frequency of attack. Such epiphenomena may underlie the variation of social-spatial patterns found in real animals.