Random Experiment Data of Communication Topology Optimization for Three-dimensional Persistent Formation with Failure Constraint

In the random experiment, experimental instances are generated under different number of agents, formation shapes, failure types, and failure ratios. Specifically, the number of agents is 20, 30, 40, and 50 respectively, 5 different formation shapes are randomly generated in the area of 5000 * 5000 * 5000 under the same number of agents, the failure type is link loss, agent loss, and link & agent loss respectively, and the failure ratio explained is 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, and 0.50 respectively. Therefore, the total number of experimental instances is 4×5×3×10 = 600. Specifically in each experimental instance, the initial optimal communication topology without failure is obtained by CTOA-3DPF-LC, both the communication links suffering link loss and the agents suffering agent loss are randomly generated in the initial optimal communication topology, and the new communication topology under failure is obtained by the existing algorithms and ECTOA-3DPF-FC respectively. Under the same failure type, number of agents, and formation shape, the set of failure in experimental instance with higher failure ratio include that with lower failure ratio.本随机实验中，实验样本基于不同智能体（agent）数量、编队形状、故障类型与故障比例生成。具体而言，智能体数量分别取20、30、40、50；同一智能体数量下，在5000×5000×5000的三维空间区域内随机生成5种不同编队形状；故障类型分为链路丢失、智能体丢失以及链路与智能体联合丢失三类；故障比例依次设置为0.05、0.10、0.15、0.20、0.25、0.30、0.35、0.40、0.45与0.50。综上，本次实验的总样本量为4×5×3×10=600。 每个实验样本中，无故障场景下的初始最优通信拓扑由CTOA-3DPF-LC构建得到；初始最优通信拓扑内，发生链路丢失的通信链路与发生智能体丢失的智能体均随机选定；故障场景下的更新通信拓扑则分别通过现有算法与ECTOA-3DPF-FC得到。在相同故障类型、智能体数量与编队形状的前提下，故障比例更高的实验样本所包含的故障场景集合，涵盖了故障比例更低的实验样本的故障场景集合。