Reflex arc-based intelligent brain decision system and decision method

Abstract

The invention relates to a reflex arc-based intelligent brain decision system and a decision method. The decision system comprises a reflex arc decision module, an information center, a feedback module, a memory module and a model module, wherein the reflex arc decision module is used for performing conditioned reflex for an acquired decision task and outputting a decision result; the informationcenter is connected with the reflex arc decision module and used for providing external information for the reflex arc decision module; the feedback module is connected with the reflex arc decision module and used for acquiring feedback information of the reflex arc decision module; the memory module is connected with the reflex arc decision module and used for recording the decision result of thereflex arc decision module; and the model module is respectively connected with the reflex arc decision module, the feedback module and the memory module, and used for performing evolutional trainingfor the reflex arc decision module according to the feedback information and the decision result. Compared with the prior art, the system and the method provided by the invention have the advantagesof having wide adaptability, being capable of solving an island problem, and so on.

Description

technical field [0001] The invention relates to the field of computer science, in particular to a reflex arc-based intelligent brain decision-making system and a decision-making method. Background technique [0002] The development of mobile Internet, Internet of Things, AI and other technologies is pushing human beings into the era of intelligent interconnection, and information is showing explosive growth. Big data, a powerful new natural resource, is developing rapidly in terms of quantity, diversity and complexity, making screening information costs are becoming higher and higher. Predictive analysis technologies such as machine learning and deep learning can improve the ability of data insight, but in many cases decision makers cannot rely on a single decision-making method to deal with multi-dimensional digital transformation. [0003] The current decision-making system has the following deficiencies: (1) The technical system of decision-making models is complicated, ...

AI Technical Summary

Problems solved by technology

[0002] The development of mobile Internet, Internet of Things, AI and other technologies is pushing human beings into the era of intelligent interconnection, and information is showing explosive growth. Big data, a powerful new natural resource, is developing rapidly in terms of quantity, diversity and complexity, making screening information costs are getting higher and higher

Predictive analysis technologies such as machine learning and deep learning can improve the ability of data insight, but in many cases, decision makers cannot rely on a single decision-making method to deal with multi-dimensional digital transformation

[0003] The current decision-making system has the following deficiencies: (1) The technical system of the decision-making model is complicated, the service forms are different, the phenomenon of decision-making islands is obvious, and it is difficult to comprehensively use multiple models; The decision-making system has obvious duplication of work; (3) The concepts used in decision-making are relatively highly specialized, and communication and sharing are difficult, which is not conducive to giving full play to collective advantages; (4) The decision-making system is incomplete and only focuses on making decisions, which affects the effect of decision-making. Insufficient consideration of evaluation, actual feedback tracking, and continuous evolution of decision-making

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