From a76275905fccdb7d22f8f8ac661295357262c031 Mon Sep 17 00:00:00 2001 From: Evolutionary-Intelligence <78018333+Evolutionary-Intelligence@users.noreply.github.com> Date: Fri, 6 Dec 2024 01:34:38 +0800 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 844efc430..2d238a900 100644 --- a/README.md +++ b/README.md @@ -105,10 +105,10 @@ particular instances of problems.](https://tinyurl.com/4yccr5k8)"---**Yurii Nest "[Optimization algorithms are often designed for a specific type of search space, exploiting its specific structure.](https://www.jmlr.org/papers/volume18/14-467/14-467.pdf)" -******* *** ******* -* ![lso](https://img.shields.io/badge/***-lso-orange.svg): indicates the specific BBO version for - **LSO** (e.g., dimension > 100, but not an absolutely deterministic number, depending upon - problems and time), +******* *** ******* ******* *** ******* ******* *** ******* ******* *** ******* +* ![lso](https://img.shields.io/badge/***-lso-orange.svg): indicates the specific BBO version + in particular for **LSO** (e.g., dimension >> 100, but not an absolutely deterministic + number, depending upon the concrete problem and time), * ![c](https://img.shields.io/badge/**-c-blue.svg): indicates the **competitive** or **de facto** BBO version for *small- or medium-dimensional* problems (though it may also work well under some certain LSO circumstances), @@ -120,7 +120,7 @@ Note that this above classification based on only the dimension of objective fun very rough* estimation for **algorithm selection**. In practice, perhaps the **simplest** way to algorithm selection is **trial-and-error**. Otherwise, you can try more advanced [Automated Algorithm Selection](https://doi.org/10.1162/evco_a_00242) techniques. -******* *** ******* +******* *** ******* ******* *** ******* ******* *** ******* ******* *** ******* Clearly, this is an **algorithm-centric** rather than benchmarking-centric Python library only for black-box optimization, though proper benchmarking is also crucial for BBO, as shown below.