[DOC] Update readme

README.md

@@ -3,9 +3,22 @@
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
 [![ABL-Package-CI](https://github.com/AbductiveLearning/ABL-Package/actions/workflows/build-and-test.yaml/badge.svg?branch=Dev)](https://github.com/AbductiveLearning/ABL-Package/actions/workflows/build-and-test.yaml)
 
-# ABL Package
+# ABL-Package
 
-This is the code repository of abductive learning Package.
+**ABL-Package** is an open source library for **Abductive Learning**. 
+Abductive learning (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. 
+
+Key Features of ABL-Package:
+
+- **Great Flexibility**: Adaptable to a variety of machine learning modules and logical reasoning components.
+- **User-Friendly**: Provide data, model, and KB, and get started with just a few lines of code.
+- **High-Performance**: Optimization for high accuracy and fast training speed.
+
+ABL-Package encapsulates advanced ABL techniques, providing users with
+an efficient and convenient package to develop dual-driven ABL systems 
+that leverage both data and knowledge.
 
 To learn how to use it, please refer to - [document](https://www.lamda.nju.edu.cn/abl_test/docs/build/html/Overview/Abductive-Learning.html).
 

docs/README.rst

@@ -1,12 +1,20 @@
 ABL-Package
 ===========
 
-**ABL-Package** is an open source library for **Abductive Learning**
-that supports building a model leveraging information from both data and
-(logical) domain knowledge. Using ABL-Package, users may form a
-dual-driven (data & knowledge driven) learning system, integrating and
-balancing the use of machine learning and logical reasoning in a unified
-model.
+**ABL-Package** is an open source library for **Abductive Learning**. 
+Abductive learning (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. 
+
+Key Features of ABL-Package:
+
+- **Great Flexibility**: Adaptable to a variety of machine learning modules and logical reasoning components.
+- **User-Friendly**: Provide data, model, and KB, and get started with just a few lines of code.
+- **High-Performance**: Optimization for high accuracy and fast training speed.
+
+ABL-Package encapsulates advanced ABL techniques, providing users with
+an efficient and convenient package to develop dual-driven ABL systems 
+that leverage both data and knowledge.
 
 .. image:: img/ABL.png