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Does the Field of Nature-Inspired Computing Contribute to Achieving Lifelike Features?
Université de Sherbrooke Multiobjective Optimization Research Lab, Department of Electrical Engineering and Computer Engineering, Canada.ORCID iD: 0000-0002-1319-513X
2023 (English)In: Artificial Life, ISSN 1064-5462, E-ISSN 1530-9185, Vol. 29, no 4, p. 487-511Article in journal (Refereed) Published
Abstract [en]

The main idea behind artificial intelligence was simple: what if we study living systems to develop new, practical computing systems that possess “lifelike” properties? And that’s exactly how evolutionary computing emerged. Researchers came up with ideas inspired by the principles of evolution to develop intelligent methods to tackle hard problems. The efficacy of these methods made researchers seek inspiration in living organisms and systems and extend the evolutionary concept to other nature-inspired ideas. In recent years, nature-inspired computing has exhibited an exponential increase in the number of algorithms that are presented each year. Authors claim that they are inspired by a behavior found in nature to come up with a lifelike algorithm. However, the mathematical background does not match the behavior in the majority of these cases. Thus the question is, do all nature-inspired algorithms remain lifelike? Also, are there any ideas included that contribute to computing? This study aims to (a) present some nature-inspired methods that contribute to achieving lifelike features of computing systems and (b) discuss if there is any need for new lifelike features.

Place, publisher, year, edition, pages
MIT Press, 2023. Vol. 29, no 4, p. 487-511
Keywords [en]
evolutionary operators, lifelike features, Nature-inspired algorithms, nature-inspired computing, nature-inspired mechanisms, Biomimetics, Computing system, Evolutionary computing, Lifelike feature, Nature inspired algorithms, Nature inspired computing, Nature-inspired mechanism, Practical computing, Property, Simple++, Evolutionary algorithms, algorithm, artificial intelligence, Algorithms
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-63821DOI: 10.1162/artl_a_00407ISI: 001135644200002PubMedID: 37463361Scopus ID: 2-s2.0-85181761154OAI: oai:DiVA.org:hj-63821DiVA, id: diva2:1846371
Available from: 2024-03-22 Created: 2024-03-22 Last updated: 2024-03-22Bibliographically approved

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Tzanetos, Alexandros

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