Biologically Inspired Computing, 2nd Edition
A special issue of Mathematics (ISSN 2227-7390).
Deadline for manuscript submissions: closed (20 May 2024) | Viewed by 1910
Special Issue Editors
Interests: computational intelligence; optimization simulation; multicriteria decision analysis; logistics and supply chain management; evolutionary computation
Special Issues, Collections and Topics in MDPI journals
Interests: cloud computing; network security; big data modeling and optimization
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Interests: swarm intelligence; evolutionary computation; big data optimization
Special Issues, Collections and Topics in MDPI journals
Interests: biocomputing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: multicriteria decision making; decision support systems; metaheuristic-based optimization; soft computing; reliability and risk analysis; rough set theory; hesitant set; soft set theory
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Special Issue Information
Dear Colleagues,
BIC, short for biologically inspired computing, is a field of study that loosely combines the related subfields of connectionism, social behavior, and emergence. It is often closely related to the field of artificial intelligence, as many of its goals can be linked to machine learning. It is also closely related to the fields of biology, computer science and mathematics. In short, it is the use of computers to simulate the phenomena of life and to improve the use of computers by studying living things. Biologically inspired computing is a major subset of natural computing. Biologically inspired computing is different from traditional artificial intelligence (AI) in that it uses a more evolved learning method instead of the so-called "creation theory" method in traditional artificial intelligence.
The purpose of this Special Issue is to gather a collection of articles that cover the latest developments in different fields of biologically inspired computing, evolutionary algorithms, biodegradability prediction, cellular automaton, the neural network, and others.
Prof. Dr. Thomas Hanne
Prof. Dr. Zhihua Cui
Dr. Gai-Ge Wang
Prof. Dr. Linqiang Pan
Dr. Harish Garg
Guest Editors
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Keywords
- biologically inspired computing
- evolutionary algorithms
- biodegradability prediction
- cellular automaton
- the neural network
- artificial immune system
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