Conditionals support in binary expression tree based genetic programming
學年 110
學期 2
發表日期 2022-03-07
作品名稱 Conditionals support in binary expression tree based genetic programming
著者 Feng-Cheng Chang; Hsiang-Cheh Huang
會議名稱 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech)
會議地點 Osaka, Japan
摘要 Inspired by the genetic algorithm (GA), the genetic programming (GP) was proposed for searching a program that fits a certain behavior. There are many aspects that distinguish GP from GA a lot, though GP concepts were originating from GA. In this paper, we focus on the representation scheme for a GP program. A GP program contains both operators and operands. Without proper encoding, the GP crossover and mutation are likely to produce invalid programs. Based on our previous design experiences, we proposed an alternative approach. It is a binary expression tree based representation with conditional behavior of each node. Therefore, the scheme supports unary, binary, and ternary operators. It also reduce the probability of producing invalid programs. A feature of the scheme is that conditional operators are first-class member because each evaluation embeds conditional processing. A few image-processing experiments were conducted to show the effectiveness of the design. The experimental results are also discussed in this paper.
語言 en_US
會議性質 國際
研討會時間 20220307~20220309
國別 JPN

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