v0.9.0
Highlights
CMA-ES with Margin is now available. It introduces a lower bound on the marginal probability associated with each discrete dimension so that samples can avoid being fixed to a single point. It can be applied to mixed spaces of continuous (float) and discrete (including integer and binary). This algorithm is proposed by Hamano, Saito, @nomuramasahir0 (a maintainer of this library), and Shirakawa, has been nominated as best paper at GECCO'22 ENUM track.
CMA-ES CMA-ESwM The above figures are taken from EvoConJP/CMA-ES_with_Margin.
Please check out the following examples for the usage.
What's Changed
- Running benchmark of Warm Starting CMA-ES on GitHub Actions. by @c-bata in #99
- Validate bounds domain contains mean by @c-bata in #100
- Fix overflow errors uncovered by Coverage-guided Fuzzing. by @c-bata in #104
- Fuzzing for sep-CMA-ES by @c-bata in #105
- Set license_file on setup.cfg by @c-bata in #106
- fix sep-CMA description by @nomuramasahir0 in #107
- Temporarily disable a GitHub action for kurobako benchmarks by @c-bata in #113
- Fix mutable by @nomuramasahir0 in #112
- Run tests with Python 3.10 by @c-bata in #109
- Update author and maintainer package info. by @c-bata in #116
- Introduce some related projects on README by @c-bata in #118
- Migrate the project metadata to pyproject.toml by @c-bata in #119
- Revert #119 to support Python 3.6. by @c-bata in #122
- Support CMA-ES with Margin. by @knshnb in #121
- Add integer examples for CMA-ES with Margin by @nomuramasahir0 in #125
- Support Python 3.11 by @c-bata in #123
- Add README of CMA-ES with margin by @knshnb in #124
- Follow-up #126: Remove Scipy dependency by @c-bata in #127
- Remove SciPy dependency by @amylase in #126
- Use gh instead of ghr by @c-bata in #128
- Bump the version up to v0.9.0 by @c-bata in #129
New Contributors
References
Full Changelog: v0.8.2...v0.9.0