no code implementations • 17 May 2024 • Kento Uchida, Ryoki Hamano, Masahiro Nomura, Shota Saito, Shinichi Shirakawa
This optimization setting is known as safe optimization and formulated as a specialized type of constrained optimization problem with constraints for safety functions.
1 code implementation • 16 May 2024 • Ryoki Hamano, Shota Saito, Masahiro Nomura, Kento Uchida, Shinichi Shirakawa
CatCMA updates the parameters of the joint probability distribution in the natural gradient direction.
no code implementations • 1 May 2023 • Yohei Watanabe, Kento Uchida, Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa
The margin correction has been applied to ($\mu/\mu_\mathrm{w}$,$\lambda$)-CMA-ES, while this paper introduces the margin correction into (1+1)-CMA-ES, an elitist version of CMA-ES.
1 code implementation • 19 Dec 2022 • Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa
If the CMA-ES is applied to the MI-BBO with straightforward discretization, however, the variance corresponding to the integer variables becomes much smaller than the granularity of the discretization before reaching the optimal solution, which leads to the stagnation of the optimization.
2 code implementations • 26 May 2022 • Ryoki Hamano, Shota Saito, Masahiro Nomura, Shinichi Shirakawa
If the CMA-ES is applied to the MI-BBO with straightforward discretization, however, the variance corresponding to the integer variables becomes much smaller than the granularity of the discretization before reaching the optimal solution, which leads to the stagnation of the optimization.