ABLkit:a Python toolkit for abductive learning  

作　　者：Yu-Xuan HUANG Wen-Chao HU En-Hao GAO Yuan JIANG 

机构地区：[1]National Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210023,China [2]School of Artificial Intelligence,Nanjing University,Nanjing 210023,China

出　　处：《Frontiers of Computer Science》2024年第6期289-290,共2页计算机科学前沿（英文版）

基　　金：JiangsuSF(BK20232003)。

摘　　要：1 Introduction.The integration of machine learning and logical reasoning has long been considered a holy grail problem in artificial intelligence.Recent years have seen considerable attention and significant progress in this field.ABductive Learning(ABL)[1,2]is a groundbreaking paradigm that integrates machine learning and logical reasoning in a unified framework.In ABL,the learning model learns to convert data into primitive logic facts,which serve as inputs for logical reasoning.

关 键 词：HAS LEARNING REASONING 

分 类 号：TP312.1[自动化与计算机技术—计算机软件与理论]