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Learning of human-like algebraic reasoning using deep feedforward neural networks

文献类型：期刊论文

作者Cai, Cheng-Hao1; Xu, Yanyan2; Ke, Dengfeng3; Su, Kaile4
刊名BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES
出版日期2018-08-01
卷号25页码:43-50
关键词Reasoning-based learning Deep learning Algebraic reasoning Neural network reasoning
ISSN号2212-683X
DOI10.1016/j.bica.2018.07.004
通讯作者Xu, Yanyan(xuyanyan@bjfu.edu.cn)
英文摘要Human-like rewriting, which is an algebraic reasoning system imitating human intelligence of problem solving, is proposed in this work. In order to imitate both learning and reasoning aspects of human cognition, a deep feedforward neural network learns from algebraic reasoning examples produced by humans and then uses learnt experiences to guide other reasoning processes. This work shows that the neural network can learn human's behaviours of solving mathematical problems, and it can indicate suitable directions of reasoning, so that intelligent and heuristic reasoning can be performed. Moreover, human-like rewriting bridges the gap between symbolic reasoning and biologically inspired machine learning. To enable the neural network to recognise patterns of symbolic expressions with non-deterministic sizes, the expressions are reduced to partial tree representations and then vectorised as numeric features. Further, the centralisation method, symbolic association vectors and rule application records are used to improve the vectorised features. With these approaches, human-like rewriting shows satisfactory performance on the tasks of solving linear equations and computing derivations and indefinite integrals.
WOS关键词TERM REWRITING-SYSTEMS
资助项目Fundamental Research Funds for the Central Universities[2016JX06] ; National Natural Science Foundation of China[61472369]
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000447096500006
出版者ELSEVIER SCIENCE BV
资助机构Fundamental Research Funds for the Central Universities ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/28118]  
专题模式识别国家重点实验室_智能交互
通讯作者Xu, Yanyan
作者单位1.Univ Auckland, Dept Comp Sci, 38 Princes St, Auckland 1142, New Zealand
2.Beijing Forestry Univ, Sch Informat Sci & Technol, 35 Qing Hua East Rd, Beijing 100083, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 95 Zhong Guan Cun East Rd, Beijing 100190, Peoples R China
4.Griffith Univ, Inst Integrated & Intelligent Syst, 170 Kessels Rd, Nathan, Qld 4111, Australia
推荐引用方式
GB/T 7714		 Cai, Cheng-Hao,Xu, Yanyan,Ke, Dengfeng,et al. Learning of human-like algebraic reasoning using deep feedforward neural networks[J]. BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES,2018,25:43-50.
APA Cai, Cheng-Hao,Xu, Yanyan,Ke, Dengfeng,&Su, Kaile.(2018).Learning of human-like algebraic reasoning using deep feedforward neural networks.BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES,25,43-50.
MLA Cai, Cheng-Hao,et al."Learning of human-like algebraic reasoning using deep feedforward neural networks".BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES 25(2018):43-50.

入库方式： OAI收割

来源：自动化研究所

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