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An autonomous cognitive development system and method based on an incremental associated neural network and dynamic audio-visual fusion

A neural network, incremental technology, applied in the field of autonomous cognitive development systems, can solve problems such as inapplicable restoration of object representation, and achieve the effect of resolving conflict associations

Active Publication Date: 2019-04-26
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Third, robots cannot develop cognition and establish a common knowledge base with humans through human-computer interaction
This method is computationally simple and consumes less memory, but is not suitable for restoring object representations

Method used

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  • An autonomous cognitive development system and method based on an incremental associated neural network and dynamic audio-visual fusion
  • An autonomous cognitive development system and method based on an incremental associated neural network and dynamic audio-visual fusion
  • An autonomous cognitive development system and method based on an incremental associated neural network and dynamic audio-visual fusion

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Embodiment 1

[0075] In one or more embodiments, an autonomous cognitive development system based on an incremental associative neural network and dynamic audio-visual fusion is disclosed, which consists of a three-layer network and can learn visual features and audio names of objects online. During learning, the structure starts from an empty network and autonomously develops concrete and abstract object concepts. Furthermore, it simultaneously establishes the association between visual features and names. System block diagram as figure 1 shown. In the visual pathway, the two sample layers learn the original shape and color features of objects, respectively, and simulate the brain's mechanism for extracting and partitioning storage of object features. A symbol layer takes the self-organized results of the shape and color sample layers and abstracts them into corresponding symbols. In the auditory pathway, a sample layer learns word vectors for names, and a symbolic layer reduces the wor...

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Abstract

The invention discloses an autonomous cognitive development system and method based on an incremental association neural network and dynamic audio-visual fusion. The system comprises a sample layer, asymbol layer and an association layer three-layer network structure, Wherein the three-layer network structure comprises a visual path and an auditory path; In the visual path, a sample layer learnsthe original shape and color characteristics of an object respectively and performs autonomous clustering; The symbol layer is used for receiving the autonomous clustering result of the shape and color sample layer and abstracting the autonomous clustering result into a corresponding symbol; In the auditory path, a sample layer learns word vectors of names; The symbol layer is used for receiving the word vector category of the name and simplifying the word vector category into symbols; And the association layer establishes an association relationship between symbols in the visual path and theauditory path, and feeds back a response signal to the low-layer network according to the known association relationship. Based on the self-organizing neural network, the concepts of objects can be autonomously developed, and audio-visual fusion can be realized.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to an autonomous cognitive development system and method based on incremental correlation neural network and dynamic audio-visual fusion. Background technique [0002] With more and more robots participating in human's daily life, cognitive development has become a hot spot in the field of intelligent robotics. Robots need to have the ability to recognize and understand when communicating with humans, so it is necessary to establish a common knowledge base with humans, such as the concept of objects. Robots are usually represented by human pre-designed internal knowledge, unable to adapt to unknown and dynamic environments. To solve this problem, robots need to have the ability to develop cognition autonomously like human babies. [0003] Using their own cognitive principles and parental guidance, human infants can rapidly develop representations of the world ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00G06N3/04G06N3/08
CPCG06N3/008G06N3/08G06N3/045
Inventor 马昕黄珂荣学文宋锐田新诚李贻斌
Owner SHANDONG UNIV
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