Learning deep IA bidirectional intelligence

被引:3
作者
Xu, Lei [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Ctr Cognit Machines & Computat Hlth CMaCH, Shanghai 200240, Peoples R China
[2] Brain & Intelligence Sci Tech Inst, Zhangjiang Lab, Neural Computat Res Ctr, Shanghai 201210, Peoples R China
关键词
Abstraction; Least mean square error reconstruction (Lmser); Cognition; Image thinking; Abstract thinking; Synthesis reasoning; TP18;
D O I
10.1631/FITEE.1900541
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There has been a framework sketched for learning deep bidirectional intelligence. The framework has an inbound that features two actions: one is the acquiring action, which gets inputs in appropriate patterns, and the other is A-S cognition, derived from the abbreviated form of words abstraction and self-organization, which abstracts input patterns into concepts that are labeled and understood by self-organizing parts involved in the concept into structural hierarchies. The top inner domain accommodates relations and a priori knowledge with the help of the A-I thinking action that is responsible for the accumulation-amalgamation and induction-inspiration. The framework also has an outbound that comes with two actions. One is called I-S reasoning, which makes inference and synthesis (I-S) and is responsible for performing various tasks including image thinking and problem solving, and the other is called the interacting action, which controls, communicates with, and inspects the environment. Based on this framework, we further discuss the possibilities of design intelligence through synthesis reasoning.
引用
收藏
页码:558 / 562
页数:5
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