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Frontiers of Information Technology & Electronic Engineering >> 2020, Volume 21, Issue 4 doi: 10.1631/FITEE.1900541

Learning deep IA bidirectional intelligence

1. Centre for Cognitive Machines and Computational Health (CMaCH), School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2. Neural Computation Research Centre, Brain and Intelligence Sci-Tech Institute, Zhangjiang Lab, Shanghai 201210, China

Available online: 2020-05-13

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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.

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