A Logical Transformation Method of the Motion Rules for Swarms
Jingjing Tao, Xiaomin Zhu, Li Ma, Meng Wu, Xiaoqing Li, Liyuan Niu · 2021
Swarm intelligence involves designing appropriate rules which make swarms with the same limited ability organize themselves to accomplish desired tasks. Numerous studies have designed many different motion rules. According to a designed rule, a swarm can self-organize into a desired pattern, such as a gathering pattern or a flocking pattern. However, for swarms that need to complete multiple tasks, it tends to be not enough to devise motion rules of forming a single pattern. Therefore, this paper presents a logical transformation method of motion rules for swarms, which essentially matches different motion rules to corresponding conditional states. The method consists of two steps: the construction of the set of conditional states and the set of motion rules, and the matching optimization calculation using genetic programming. The feasibility of this method is verified by simulations.