Learning deep IA bidirectional intelligence

XU Lei

doi:10.1631/FITEE.1900541

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Learning deep IA bidirectional intelligence

Regular Papers | Updated：2022-05-19

- Learning deep IA bidirectional intelligence
- 深度IA双向智能
- Frontiers of Information Technology & Electronic Engineering Vol. 21, Issue 4, Pages: 558-562(2020)
- Affiliations：
  
  Centre for Cognitive Machines and Computational Health (CMaCH), School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  Neural Computation Research Centre, Brain and Intelligence Sci-Tech Institute, Zhangjiang Lab, Shanghai 201210, China
- Author bio：
  
  [ "Lei XU, E-mail: lxu@cs.sjtu.edu.cn" ]
- Funds：
- DOI：10.1631/FITEE.1900541
  CLC： TP18
- Received：30 September 2019，
  
  Revised：2019-12-23，
  
  Published：2020-04
- Accepted：
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XU Lei. Learning deep IA bidirectional intelligence[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(4): 558-562.
DOI：

XU Lei. Learning deep IA bidirectional intelligence[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(4): 558-562. DOI： 10.1631/FITEE.1900541.

摘要

Abstract

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.

关键词

Keywords

references

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