肖人彬1，邬博文1，赵嘉2，陈峙臻3
1.华中科技大学人工智能与自动化学院；
2. 南昌工程学院信息工程学院；
3. 格林威治大学商学院
摘要：聚焦高等生物，从涵盖群智能和众智能的群体智能整体视角，对仿生计算中存在的问题进行分析并展开综合性评述，提出并阐释若干新的观点和见解。在对高等生物（涉及基本高等生物、常规高等生物和类人高等生物）仿生计算研究进展进行概述的基础上，针对群智能优化中以“动物园算法”为标志的造算法之风，发现研究中出现的回流现象，从仿生-计算维度和问题-方法维度对造算法之风的形成原因给予合理解读。进而给出解决问题的整体思路，提炼形成群体智能仿生计算的两个主要发展方向，强调仿生行为向合作行为方向的拓展在群体智能仿生计算发展方向上处于主导地位；针对群智能优化研究存在的困难，提出需要重点发力实现突破的5个瓶颈问题；基于“隐喻式仿生计算-规范仿生计算-复杂仿生计算”的整体视图，倡导复杂仿生计算的智能计算新范式，为高等生物仿生计算引领方向。
关键词：群体智能;仿生计算;合作行为;灵长类;动物园算法;智能计算范式
基金资助：科技创新2030—“新一代人工智能”重大项目(2018AAA0101200)
![]()
Bionic Computing in Higher
Organisms from the Perspective of Collective
Intelligence: Problem Analysis and Comprehensive Review
XIAO Renbin1, WU Bowen1,
ZHAO Jia2, CHEN Zhizhen31.
School of Artificial Intelligence and Automation, Huazhong University of
Science and Technology; 2. School of Information
Engineering, Nanchang Institute of Technology; 3.Business
School, University of GreenwichAbstract: This paper focuses on higher
organisms. From the perspective of collective intelligence as a whole, which
encompasses swarm intelligence and crowd intelligence, this paper analyzes and
develops a comprehensive review of the problems in bionic computing, and also
proposes and explains a number of new perspectives and insights. On the basis
of an overview on the research progress of bionic computation in higher
organisms (including fundamental higher organisms, regular higher organisms and
quasi-man organisms), we find the reflux phenomenon in the research on the
trend of making algorithms in the optimization of swarm intelligence, and give
a reasonable interpretation of the reasons for the formation of the trend of
making algorithms in the bionic-computational dimension and the problem-method
dimension. In turn, the overall idea of problem solving is given, and the two
main development directions of bionic computing for collective intelligence are
refined and formed. Emphasis on the expansion of bionic behavior towards
cooperative behavior is dominant in the direction of collective intelligence
bionic computing development. Aiming at the difficulties existing in the
research of swarm intelligence optimization, five bottlenecks that need to be
focused on to achieve breakthroughs are proposed. Based on the overall view of
“metaphorical bionic computing - normative bionic computing - complex bionic
computing”, we advocate the new paradigm of intelligent computing of complex bionic
computing, and lead the direction for higher organism bionic computing.Keywords: collective intelligence; bionic computing; cooperative
behavior; primate; zoo algorithm; intelligent computing paradigm作者介绍:
肖人彬（1965-），湖北武汉人，博士，教授，博士生导师。主要研究方向为群体智能、大规模个性化定制、复杂产品创新设计、网络舆情传播与治理等。作为第一完成人获得教育部自然科学奖二等奖、湖北省科技进步奖二等奖和3项湖北省自然科学奖，主持承担11项国家自然科学基金，在国内外学术期刊发表300多篇论文。
![]()
邬博文(1997-)，湖北武汉人，博士研究生,主要研究方向为群体智能和无人系统。
![]()
赵嘉（1981-），安徽桐城人，博士，教授,主要研究方向为从事群体智能、大数据分析、人工智能理论与应用等。发表学术期刊论文150余篇。
![]()
陈峙臻(1986-)，博士,英国格林威治大学商学院高级讲师，主要研究方向为机器学习算法、金融风险管理等。引用本文:
肖人彬，邬博文，赵嘉，陈峙臻.群体智能视角下的高等生物仿生计算：问题分析与综合评述[DB/OL].(2024-12-23).http://kns.cnki.net/kcms/detail/37.1402.N.20241220.1713.002.html.
↓↓↓全文请点下方阅读原文
