Special Issue on Interdisciplinary Artificial Intelligence: Methods and Applications of Nature-Inspired Computing

Inspiration in nature has been widely explored, from the macro to micro-scale. From a scientific perspective, these methods inspired by nature have proven to be efficient tools for tackling real-world problems because most of the latter are highly complex or the resources are limited to analyze them. This inspiration is justified by the fact that natural phenomena mainly emphasize adaptability, optimization, robustness, and organization, among other properties, to deal with complexity. In that sense, three methodologies are commonly considered: human-designed problem-solving techniques inspired by nature, the synthesis of natural phenomena to develop algorithms, and the use of nature-inspired materials to perform computations. Some applications of nature-inspired computing include data mining, machine learning, optimization, robotics, engineering control systems, human–machine interaction, healthcare, the Internet of Things, cloud computing, smart cities, and many others.|| This Special Issue aimed to cover original research works with emphasis on the methodologies and applications of nature-inspired computing to handle the above-mentioned complex systems. We received a total of 38 submitted papers, and 18 papers were accepted (covering 47% of acceptance rate).|| The Special Issue presents different works related to metaheuristic optimization methods and their applications of human brain inspiration and neural networks, natural language processing-based applications, and fuzzy-logic-based applications. ©2022 Applied Sciences, MDPI.