生物启发计算研究现状与发展趋势
Research Status and Development Trends of the Bio-inspired Computation
查看参考文献80篇
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文摘
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生物启发计算的宗旨是研究自然界生物个体、群体、群落乃至生态系统不同层面的功能、特点和作用机制,建立相应的模型与计算方法,从而服务于人类社会的科学研究与工程应用.它既是人工智能的继承与发展,同时也是从新的角度理解和把握智能本质的方法.本文阐述了生物启发计算所涉及的生物进化论、共生进化论和复杂适应系统的理论起源.在对生物启发计算进行分析、归纳和总结的基础上,介绍了现有生物启发计算算法研究成果,并从最优设计、最优分析和最优控制3个方面对生物启发计算的应用研究成果进行了梳理.以此为基础,进一步地提出了生物启发计算的统一框架模型.最后,围绕并行生物启发计算、具有学习推理和知识学习生物启发计算、生物动力学启发计算、基于微生物群体感应的生物启发计算以及人工大脑、进化硬件、大数据、群集机器人、虚拟生物和云计算等前沿热点理论问题和工程应用问题对生物启发计算的发展方向和研究挑战进行了展望及分析. |
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其他语种文摘
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Bio-inspired computation aims to study the biology function,characteristic and mechanism of the various levels of nature,from biological individual,population,colony until ecosystem,and set up a relevant model and computing method,so as to serve the scientific research and engineering application of human society. It is not only the inheritance and development of artificial intelligence,but also from a new point to understand and grasp the intelligent intrinsic. First,we introduce the bio-inspired computation theoretical origin,involving the biological evolutionism theory,the symbiosis evolution theory and the complex adaptive system theory. Then,we review algorithm research progress and discuss about application research progress from three aspects including optimal plan,optimal analysis and optimal control. Based on comprehensive analysis and summarize existing bio-inspired optimization algorithms,a bio-inspired computation unified framework model is proposed. Finally,a few future directions and research challenges are presented,such as parallel bio-inspired computation,bio-inspired computation with reasoning and knowledge,bio-inspired dynamics computation, bio-inspired computation based on quorum sensing,artificial brain,evolutionary hardware,big data, swarm robot,virtual biological,cloud computing,etc. |
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来源
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信息与控制
,2016,45(5):600-614,640 【核心库】
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DOI
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10.13976/j.cnki.xk.2016.0600
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关键词
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生态系统
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复杂适应系统
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涌现
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生物启发计算
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优化计算
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地址
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中国科学院沈阳自动化研究所, 机器人学国家重点实验室, 辽宁, 沈阳, 110016
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沈阳师范大学物理科学与技术学院, 辽宁, 沈阳, 110034
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天津工业大学计算机科学与软件学院, 天津, 300387
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1002-0411 |
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学科
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自动化技术、计算机技术 |
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基金
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国家自然科学基金资助项目
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文献收藏号
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CSCD:5871050
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