摘要
为研究一维二值元胞自动机的一类重要的群体演化行为——准周期三行为,提出了基于离散粒子群的元胞自动机演化算法,并通过使用活性元胞迭代图的平均面积为适值函数,发现了具有准周期三行为的元胞规则。与遗传算法相比,基于离散粒子群的元胞演化算法的搜索效率更高。实验还进一步表明,准周期三行为是某些元胞规则的特定行为,一定条件下与元胞自动机的初始构型关系不大。
In order to research a non-trivial swarm behavior （ quasiperiod-3 behavior） of one-dimension two-value cellular automata, a new method using the binary particle swarm to evolve cellular automata is addressed. By choosing the average area in the iterative map as the fitness function, we found several satisfied rules. Compared with the genetic algorithm, the binary particle swarm optimization algorithm is more effective. The result also shows that quasiperiod-3 behavior is some cellular automata rule＇s specialized behavior which has little relation with its initial construction.
出处
《复杂系统与复杂性科学》
EI
CSCD
2007年第4期25-31,共7页
Complex Systems and Complexity Science
基金
国家自然科学基金(60573124
60574011)
辽宁省教育厅基金项目资助(202283426)
关键词
离散粒子群优化算法
元胞自动机
准周期三行为
binary particle swarm optimization （BPSO）
cellular automata （CA）
quasiperiod-3 behavior （ QP3 ）
