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Nature-Inspired Intelligent Computing: A Comprehensive Survey.

التفاصيل البيبلوغرافية
العنوان: Nature-Inspired Intelligent Computing: A Comprehensive Survey.
المؤلفون: Jiao L; School of Artificial Intelligence, Xidian University, Xi'an, China., Zhao J; School of Artificial Intelligence, Xidian University, Xi'an, China., Wang C; School of Artificial Intelligence, Xidian University, Xi'an, China., Liu X; School of Artificial Intelligence, Xidian University, Xi'an, China., Liu F; School of Artificial Intelligence, Xidian University, Xi'an, China., Li L; School of Artificial Intelligence, Xidian University, Xi'an, China., Shang R; School of Artificial Intelligence, Xidian University, Xi'an, China., Li Y; School of Artificial Intelligence, Xidian University, Xi'an, China., Ma W; School of Artificial Intelligence, Xidian University, Xi'an, China., Yang S; School of Artificial Intelligence, Xidian University, Xi'an, China.
المصدر: Research (Washington, D.C.) [Research (Wash D C)] 2024 Aug 16; Vol. 7, pp. 0442. Date of Electronic Publication: 2024 Aug 16 (Print Publication: 2024).
نوع المنشور: Journal Article; Review
اللغة: English
بيانات الدورية: Publisher: American Association for the Advancement of Science Country of Publication: United States NLM ID: 101747148 Publication Model: eCollection Cited Medium: Internet ISSN: 2639-5274 (Electronic) Linking ISSN: 26395274 NLM ISO Abbreviation: Research (Wash D C) Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [Washington, DC] : [China] : American Association for the Advancement of Science ; Science and Technology Review Publishing House, [2018]-
مستخلص: Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms. Over the past decades, these paradigms have revealed effective and flexible solutions to practical and complex problems. This paper summarizes the natural mechanisms of diverse advanced nature-inspired intelligent computing paradigms, which provide valuable lessons for building general-purpose machines capable of adapting to the environment autonomously. According to the natural mechanisms, we classify nature-inspired intelligent computing paradigms into 4 types: evolutionary-based, biological-based, social-cultural-based, and science-based. Moreover, this paper also illustrates the interrelationship between these paradigms and natural mechanisms, as well as their real-world applications, offering a comprehensive algorithmic foundation for mitigating unreasonable metaphors. Finally, based on the detailed analysis of natural mechanisms, the challenges of current nature-inspired paradigms and promising future research directions are presented.
Competing Interests: Competing interests: The authors declare that they have no competing interests.
(Copyright © 2024 Licheng Jiao et al.)
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تواريخ الأحداث: Date Created: 20240819 Latest Revision: 20240820
رمز التحديث: 20240820
مُعرف محوري في PubMed: PMC11327401
DOI: 10.34133/research.0442
PMID: 39156658
قاعدة البيانات: MEDLINE
الوصف
تدمد:2639-5274
DOI:10.34133/research.0442