Paper Info
Title
Designing Fitness Functions for Evolutionary Optimization of the System Inspired by Pattern Formation in Morphogenesis.
Abstract
The morphogenetie engineering that learns biological morphogenesis has attracted our attention recently. In the paper, we first propose a new system that models pattern formation in biological morphogenesis. The system is theoretically able to produce a variety of shapes similar to desired one. However, to realize that, it is necessary to optimize parameters of the system. So, we assume the use of an evolutionary algorithm for the optimization and examine a suitable fitness function for the optimization through simulations. The simulation results reveal that the suitable fitness function enables the evolutionary algorithm to find parameters that produce a variety of rough shapes including the desired one at the top priority and then to conduct fine-tuning of parameters for obtaining closer shapes to the desired one.
Year
DOI
Venue
2018
10.1109/SCIS-ISIS.2018.00053
Joint International Conference on Soft Computing and Intelligent Systems SCIS and International Symposium on Advanced Intelligent Systems ISIS
Field
DocType
ISSN
Computer science,Pattern formation,Artificial intelligence,Machine learning,Morphogenesis
Conference
2377-6870
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Kei Ohnishi13917.71