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http://dx.doi.org/10.9708/jksci.2021.26.09.027

Simulation of Sustainable Co-evolving Predator-Prey System Controlled by Neural Network  

Lee, Taewoo (Program in Visual Information Processing, Korea University)
Kim, Sookyun (Dept. Computer Engineering, Jeju National University)
Shim, Yoonsik (Dept. of Game Engineering, Pai Chai University)
Publication Information
Journal of the Korea Society of Computer and Information / v.26, no.9, 2021 , pp. 27-35 More about this Journal
Abstract
Artificial life is used in various fields of applied science by evaluating natural life-related systems, their processes, and evolution. Research has been actively conducted to evolve physical body design and behavioral control strategies for the dynamic activities of these artificial life forms. However, since co-evolution of shapes and neural networks is difficult, artificial life with optimized movements has only one movement in one form and most do not consider the environmental conditions around it. In this paper, artificial life that co-evolve bodies and neural networks using predator-prey models have environmental adaptive movements. The predator-prey hierarchy is then extended to the top-level predator, medium predator, prey three stages to determine the stability of the simulation according to initial population density and correlate between body evolution and population dynamics.
Keywords
Artificial Life; Predator-Prey; Artificial Neural Network; Simulation; Genetic Algorithm;
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Times Cited By KSCI : 1  (Citation Analysis)
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