Nature-Inspired Intelligent Computing: A Comprehensive Survey

Overview

Journal Research (Wash D C)

Specialty Biology

Date 2024 Aug 19

PMID 39156658

Authors

Licheng Jiao

Jiaxuan Zhao

Chao Wang

Xu Liu

Fang Liu

Lingling Li

Ronghua Shang

Yangyang Li

Wenping Ma

Shuyuan Yang

Affiliations

Soon will be listed here.

Abstract

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.

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