From a7c1772bdba3b0aec5c7f7aabb0b34bc13b26ce4 Mon Sep 17 00:00:00 2001 From: Gao Enhao Date: Wed, 17 Jan 2024 15:04:04 +0800 Subject: [PATCH] [MNT] modify title level in README.md --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 5ecfd0a..57411ec 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ -# ABLkit: A Python Toolkit for Abductive Learning +## ABLkit: A Python Toolkit for Abductive Learning **ABLkit** is an efficient Python toolkit for [**Abductive Learning (ABL)**](https://www.lamda.nju.edu.cn/publication/chap_ABL.pdf). ABL is a novel paradigm that integrates machine learning and logical reasoning in a unified framework. It is suitable for tasks where both data and (logical) domain knowledge are available. @@ -30,9 +30,9 @@ ABLkit encapsulates advanced ABL techniques, providing users with an efficient a ABLkit

-## Installation +### Installation -### Install from PyPI +#### Install from PyPI The easiest way to install ABLkit is using ``pip``: @@ -40,7 +40,7 @@ The easiest way to install ABLkit is using ``pip``: pip install ablkit ``` -### Install from Source +#### Install from Source Alternatively, to install from source code, sequentially run following commands in your terminal/command line. @@ -50,7 +50,7 @@ cd ABLkit pip install -v -e . ``` -### (Optional) Install SWI-Prolog +#### (Optional) Install SWI-Prolog If the use of a [Prolog-based knowledge base](https://ablkit.readthedocs.io/en/latest/Intro/Reasoning.html#prolog) is necessary, please also install [SWI-Prolog](https://www.swi-prolog.org/): @@ -62,7 +62,7 @@ sudo apt-get install swi-prolog For Windows and Mac users, please refer to the [SWI-Prolog Install Guide](https://github.com/yuce/pyswip/blob/master/INSTALL.md). -## Quick Start +### Quick Start We use the MNIST Addition task as a quick start example. In this task, pairs of MNIST handwritten images and their sums are given, alongwith a domain knowledge base which contains information on how to perform addition operations. Our objective is to input a pair of handwritten images and accurately determine their sum. @@ -187,7 +187,7 @@ bridge.test(test_data) To explore detailed tutorials and information, please refer to - [document](https://ablkit.readthedocs.io/en/latest/index.html). -## Examples +### Examples We provide several examples in `examples/`. Each example is stored in a separate folder containing a README file. @@ -196,7 +196,7 @@ We provide several examples in `examples/`. Each example is stored in a separate + [Handwritten Equation Decipherment](https://github.com/AbductiveLearning/ABLkit/tree/main/examples/hed) + [Zoo](https://github.com/AbductiveLearning/ABLkit/tree/main/examples/zoo) -## References +### References For more information about ABL, please refer to: [Zhou, 2019](http://scis.scichina.com/en/2019/076101.pdf) and [Zhou and Huang, 2022](https://www.lamda.nju.edu.cn/publication/chap_ABL.pdf).