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Self-adaptive Crossover and Mutation Parameters in Tree Adjoining Grammar Guided Genetic Programming
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hảo, Hoàng Tuấn Cảnh, Vũ Văn |
| Copyright Year | 2015 |
| Abstract | In some Evolutionary Computations such as Genetic Algorithms or Evolution Strategies, it is well known that the choice of genetic operator rates is important to the success of these algorithms. Researchers mainly focused on choosing genetic operator rates appropriate to specific problems. Several papers work on adapting crossover and mutation rate in evolutionary algorithms showing potential results that adaptive algorithms may out-perform non-adaptive ones. In this paper, we examine the application of adaptive operator selection rates to genetic programming and propose a new algorithm for self-adapting crossover and mutation rates in the specific genetic programming Tree Adjoining Grammar Guided Genetic Programming (TAG3P). Experimental results showed that our proposed algorithm improved the performance of TAG3P than previous works. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://fit.mta.edu.vn/chuyensan/Pdf_Files/042015/06_01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
