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Method for computer to simulate human brain in learning knowledge, logic theory machine and brain-like artificial intelligence service platform

A computer and knowledge technology, applied in logical reasoning machines and brain-like artificial intelligence service platforms, simulating the field of human brain learning knowledge, can solve problems such as learning and working of artificial intelligence without a computer, complete and systematic solution

Active Publication Date: 2018-11-23
HUNAN BENTI INFORMATION TECH RES CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, the patent proposal does not give information on how the computer learns knowledge and how to intelligently work and execute programs with the calculation method of judgment and reasoning. As a result, the patent does not completely and systematically address the need for artificial intelligence to learn and work in a brain-like manner. technical issues

Method used

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  • Method for computer to simulate human brain in learning knowledge, logic theory machine and brain-like artificial intelligence service platform
  • Method for computer to simulate human brain in learning knowledge, logic theory machine and brain-like artificial intelligence service platform
  • Method for computer to simulate human brain in learning knowledge, logic theory machine and brain-like artificial intelligence service platform

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specific Embodiment

[0077] Because there are only the above five kinds of logical relations in the reasoning thinking of the human brain, through the above-mentioned axiomatic rules, an analytical reasoning program can be established for any problem-solving problem, and reliable logical conclusions can be obtained through judgment and calculation. By programming and digitizing analysis and reasoning, computers can learn and work in an intelligent way of brain-like judgment and reasoning. Through the above-mentioned executable programs, the machine can obtain human-computer interaction results that meet the application requirements, ensuring the logical correctness of the output. Specific examples are as follows:

[0078] Judgment example 1: Trump is an American.

[0079] String say="Trump is an American.";

[0080] listener.MatchListener(say); / / JH platform monitoring;

[0081] JHAction jha = new JHAction();

[0082] Semanteme semanteme = jha. JHSemanteme(say);

[0083] / / Receive the grammati...

example 2

[0091] Judgment example 2: Trump is Chinese.

[0092] String say="Trump is Chinese.";

[0093] listener.MatchListener(say); / / JH platform monitoring;

[0094] JHAction jha = new JHAction();

[0095] Semanteme semanteme = jha. JHSemanteme(say);

[0096] / / Receive the grammatical components of the sentence;

[0097] int zlj=semanteme.getZlj(); / / Get the logical value of the subject in the composition,

[0098] Here the value is 1;

[0099] int wlj=semanteme.getWlj(); / / Get the logical value of the predicate in the component,

[0100] Here the value is 1;

[0101] Int[] RLV= jha.getComparison(say); / / Get the actual comparison logic value, where the value is the actual main logic value 1, and the actual predicate logic value is 0

[0102] Boolean fal=LanguagComparisonEreality(zlj,wlj,RLV);

[0103] / / Obtain the comparison value of language and scene to get the truth value of this sentence, that is, the return value is 0. Here, after the nature of the predicate has changed: i...

example 3

[0116] Reasoning example 3 (necessary and sufficient conditions): the diameter of the cup is 5 cm, which is equal to (if and only) when the cup is qualified.

[0117] String say="The diameter of the cup is 5 cm, which is equal to the qualified cup.";

[0118] JHAction jha = new JHAction();

[0119] Semanteme semanteme=jha. JHSemanteme(say);

[0120] String JudgeConditions=semanteme.getqj(); / / Get the judgment condition of the former item in the composition "the caliber of the cup is 5 cm";

[0121] Through examples 1 and 2, when we process the cup to obtain the actual caliber of the cup, it is uncertain, it may be equal to 5 cm or may not be equal to 5 cm, so the actual caliber and the standard caliber we get are uncertain, then here There are two possible return values, one for 1 and one for 0. When the return value is 1, the correct conclusion introduced here is: the cup is qualified. That is, if the antecedent of the necessary and sufficient condition is true, the conseq...

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Abstract

The invention relates to the field of computers, in particular to a method for a computer to simulate human brain in learning knowledge, a logic theory machine and a brain-like artificial intelligenceservice platform. The method for the computer to simulate human brain in learning knowledge comprises the following steps: establishing a computer brain-like knowledge base, including a lexicon, a class library, a resource library and an intelligent information management library; making the computer call a semantic analyzer to create class basic elements and semantic properties generated by a single sentence with natural language statements by a class method, and store the class basic elements and semantic properties in the class library; and making the computer call the semantic analyzer togenerate an intelligent application specific to an intelligent application demand based on intelligent knowledge elements in the class library, and store the intelligent application in the intelligent information management library. A cognitive model for the human brain to recognize objective things by intelligent calculation and judgment and the intelligent mechanism of logical reasoning based on the cognitive model are simulated to a computer system by an artificial method, thereby realizing the intelligent function of a machine to simulate human brain to study and work, and forming a brain-like artificial intelligence service platform.

Description

technical field [0001] The invention relates to the field of human computers, in particular to a method for simulating human brain learning knowledge, a logic reasoning machine and a brain-inspired artificial intelligence service platform. Background technique [0002] The ideal goal of artificial intelligence is to enable machines to learn and work in a brain-like manner. To achieve this goal, it is necessary to artificially simulate the human cognitive model and intelligent mechanism to the computer, that is, to process the data information in the computer in a brain-like way. Due to the logic proved by Gödel's incompleteness theorem and Turing's halting Due to the limitations of formal systems and mechanical computing power, this kind of brain-like artificial intelligence technology has not been realized so far. [0003] The so-called logical limitations of the proofs of Gödel's theorem and Turing's halting theorem, in layman's terms, are the proofs of their theorems, wh...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/33G06F17/27G06N5/04
CPCG06F8/33G06N5/04G06F40/30G06F40/289G06F40/295G06F40/211G06F8/30G06F8/20G06N5/022G06N5/046G06N20/00
Inventor 万继华
Owner HUNAN BENTI INFORMATION TECH RES CO LTD
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