From 6126027d0855d6f05303e76adafe3e393e968c6a Mon Sep 17 00:00:00 2001 From: Tony-HYX <605698554@qq.com> Date: Wed, 27 Dec 2023 23:25:37 +0800 Subject: [PATCH 1/3] [DOC] Update readme --- README.md | 17 +++++++++++++++-- docs/README.rst | 20 ++++++++++++++------ 2 files changed, 29 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 5b98e4b..222ca6a 100644 --- a/README.md +++ b/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). diff --git a/docs/README.rst b/docs/README.rst index 9e5494e..30bdf78 100644 --- a/docs/README.rst +++ b/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 From 431a745af1cfdd595221f0313b33a79d9064864b Mon Sep 17 00:00:00 2001 From: Tony-HYX <605698554@qq.com> Date: Wed, 27 Dec 2023 23:28:25 +0800 Subject: [PATCH 2/3] [DOC] modify readme --- README.md | 6 +++--- docs/README.rst | 6 +++--- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 222ca6a..4ccb86e 100644 --- a/README.md +++ b/README.md @@ -5,9 +5,9 @@ # ABL-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 +**ABL-Package** is an open source library for **Abductive Learning (ABL)**. +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: diff --git a/docs/README.rst b/docs/README.rst index dd14d0a..1287302 100644 --- a/docs/README.rst +++ b/docs/README.rst @@ -1,9 +1,9 @@ ABL-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 +**ABL-Package** is an open source library for **Abductive Learning (ABL)**. +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: From 0da35aba311f7eb34cd09b6d7142370c1f2b902b Mon Sep 17 00:00:00 2001 From: Tony-HYX <605698554@qq.com> Date: Wed, 27 Dec 2023 23:42:05 +0800 Subject: [PATCH 3/3] [DOC[ Minor revision of readme --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 4ccb86e..2965999 100644 --- a/README.md +++ b/README.md @@ -55,12 +55,12 @@ For Linux users: For Windows and Mac users, please refer to the [Swi-Prolog Download Page](https://www.swi-prolog.org/Download.html). -## Example -+ MNIST ADD - [here](https://github.com/AbductiveLearning/ABL-Package/blob/Dev/examples/mnist_add) -+ Hand Written Formula - [here](https://github.com/AbductiveLearning/ABL-Package/blob/Dev/examples/hwf) -+ Hand written Equation Decipherment - [here](https://github.com/AbductiveLearning/ABL-Package/tree/Dev/examples/hed) -+ Zoo - [here](https://github.com/AbductiveLearning/ABL-Package/tree/Dev/examples/zoo) - -## NOTICE -They can only be used for academic purpose. For other purposes, please contact with LAMDA Group(www.lamda.nju.edu.cn). +## Examples + +We provide several examples in `examples/`. Each example is stored in a separate folder containing a README file. + ++ [MNIST Addition](https://github.com/AbductiveLearning/ABL-Package/blob/Dev/examples/mnist_add) ++ [Hand Written Formula](https://github.com/AbductiveLearning/ABL-Package/blob/Dev/examples/hwf) ++ [Hand written Equation Decipherment](https://github.com/AbductiveLearning/ABL-Package/tree/Dev/examples/hed) ++ [Zoo](https://github.com/AbductiveLearning/ABL-Package/tree/Dev/examples/zoo)