计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210900249-7.doi: 10.11896/jsjkx.210900249
朱迪迪1, 吴超2
ZHU Di-di1, WU Chao2
摘要: 群体智能有着丰富的内涵和外延,其算法既包括早期基于生物群体特征规律的算法(粒子群优化和蚁群算法等),也包括后期基于网络互联的大规模群体算法(多智能体系统、群智感知和联邦学习等)。这些群体智能算法均蕴含着协作或对抗的核心思想。协作能够把个体的有限智慧耦合汇聚成群体的强大智能,但是协作本身具有一定的局限性,可能会导致个体间过分依赖和系统的不公平性等问题。对抗可以突破这种局限性,其基本思想是个体通过博弈等手段谋取自身最大利益。因此,协作和对抗缺一不可,以对抗促协作,协作中存对抗。通过聚焦群体智能算法的协作和对抗方法,对经典群体智能算法的思想进行阐述,并对新兴的群体智能算法的下一步发展方向进行展望,总结了构建协作与对抗并存的群体智能生态,是群体智能的必然发展趋势。
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