# Dynamic Multi-Target Self-Organization Hunting Control of Multi-Agent Systems
## 5 Simulation Analysis
From the position change graph, it can be seen that in Figure 5(1) and Figure 6(1), starting from the initial position, each agent has gradually moved toward the target direction of task allocation after 35 iteration steps. In Figure 5(2) and Figure 6(2), after 112 iteration steps, agents are already reaching the vicinity of targets 1 and 3. In Figure 5(3) and Figure 6(3), after 180 iteration steps, targets 1 and 3 are no longer visible, which indicates that the agent has reached a position close to targets 1 and 3. Figure 5(4) and Figure 6(4) shows that after 253 iteration steps, target 1 has been hunted by three agents. In Figure 5(5) and Figure 6(5), after iteration to 451 iteration steps, the three targets represented by the green pentagram can no longer be seen. In Figure 5(7) and Figure 6(7), after 1528 iteration steps, the agent formed an encirclement cluster that hunts the target. In Figure 5(8) and Figure 6(8), after 1528 until 2000 iteration steps, the agent always follows the formed bounding encirclement and moves forward with the target, without losing or leaving the target. What requires further explanation here is that the agent does not know the motion state of the target. However, the agent can adjust, step by step, its position, velocity, and acceleration through its position error, velocity error, and acceleration error, with the target under the control of the hunting control strategy, always rounding up the target at a certain safe distance. Figure 7 shows the complete trajectory of the multi-agent encirclement of dynamic multiple targets. All three targets move at a uniform speed in their respective directions. Figure 7(1) shows the hunting process of multiple dynamic targets in a 2-D environment of the multi-agent system. Compared to Figure 7(1),(2) has added a time coordinate axis. Figures 8-10 show the process and results of multi-agent subgroups surrounding targets 1, 2, and 3, respectively. In the trajectory distribution diagram in Figures 7-10, the black line shows the motion trajectory of the agent, and the green line indicates the motion trajectory of the target. Figure 4: Schematic diagram of the variation curve of iteration number and optimal task allocation evaluation factor. Figure 5: Iteration step position distribution map. (**1**) Iterative 35 step position distribution map; (**2**) Iterative 112 step position distribution map; (**3**) Iterative 180 step position distribution map; (**4**) Iterative 253 step position distribution map; (**5**) Iterative 451 step position distribution map; (**6**) Iterative 846 step position distribution map; (**7**) Iterative 1528 step position distribution map; (**8**) Iterative 2000 step position distribution map. Figure 6: The 3-D position change map. (**1**) Iterative 35 step position change map; (**2**) Iterative 112 step position change map; (**3**) Iterative 180 step position change map; (**4**) Iterative 253 step position change map; (**5**) Iterative 451 step position change map; (**6**) Iterative 846 step position change map; (**7**) Iterative 1528 step position change map; (**8**) Iterative 2000 step position change map. Figure 8: Target 1 movement process trajectory map. Figure 7: Distribution of trajectories obtained by iterating 2000 steps: **(1)** Trajectory distribution obtained through 2000 iterations in 2-D coordinates; **(2)** Trajectory distribution obtained through 2000 iterations in 3-D coordinates. Figure 9: Target 2 movement process trajectory map. Figure 11 shows the variation in the relative positions of each agent relative to their hunting target, which indicates that each agent can approach and gather around the target it has chosen. Figures 8-10 show that after successful hunting of targets 1 and 3, the comparative position of the agent relative to its target remains unchanged. In contrast, after successfully hunting target 2, the agent rotates relative to its target. The reason for this is that the number of agents around target 1 and target 3 is both three, which is an odd number.