机器推理的进展与展望

被引：8
|
作者：
丁梦远
兰旭光
彭茹
郑南宁
机构：
[1] 西安交通大学人工智能学院
来源：
模式识别与人工智能 | 2021年 / 34卷 / 01期
基金：
国家自然科学基金重点项目;
关键词：
人工智能; 机器推理; 直觉推理; 因果推理;
D O I：
10.16451/j.cnki.issn1003-6059.202101001
中图分类号：
TP181 [自动推理、机器学习];
学科分类号：
摘要：
机器学习算法的发展仍受到泛化能力较弱、鲁棒性较差、缺乏可解释性等问题的限制.文中介绍机器推理,说明推理对于机器学习人的知识和逻辑、理解和解释世界的重要作用.首先分析人类大脑推理机制,从认知地图、神经元和奖赏回路,扩展到受脑启发的直觉推理、神经网络和强化学习.进而总结机器推理的方式及其相互关联的现状、进展及挑战,具体包括直觉推理、常识推理、因果推理和关系推理等.最后展望机器推理的应用前景与未来的研究方向.
引用
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页码：1 / 13
页数：13
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