Approximating Chinese Character Pattern with Genetic Algorithm

Yaluo Wang

《International Core Journal of Engineering》 7卷9期 (2021/09) Pp. 427-434

https://doi.org/10.6919/ICJE.202109_7(9).0059

摘要

The beauty of algorithms is a type of aesthetics that is beyond the emotional expression of the colors on paint brushes. In this paper, the research is accomplished through a coding program of Python to focus on approximating the selected Chinese character pattern, represented by two dimensional binary matrices, through generations of evolutions. The implementation of Chinese character is creative by combining technology with Chinese heritage, the character. How the technology is able to generate man-made characters through coding? The known steps of the Genetic Algorithm are the Initiation of population, Mutation, Selection and Crossover. Evolution is conducted on generations of populations, in which are candidate patterns, and the learning process can be tuned with multiple parameters including the mutation rate, the mutation fraction, the maximum generations and the population size. In addition, random immigrants are further introduced when the optimization score is not improving. When the process is successful, the result shows the best fitness score of 1.0, which implies 100% of similarity between the target Chinese character pattern and generated pattern. The algorithm is able to converge despite the grid size, and other setup of parameters including maximum generations, mutation rate, population numbers, etc. Above all, the rules of Game of Life are introduced as another intriguing approach for generating patterns on top of the Genetic Algorithm but should only be considered as an alternative.

關鍵字

Genetic Algorithm ； Game of Life ； Chinese Character ； Python

參考文獻

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