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Improved hippocampus-forehead cortex network space cognition method

A technology of cyberspace and hippocampus, applied in the field of mobile robot spatial cognitive navigation model, which can solve the problems of poor performance, weak model adaptability and robustness, etc.

Pending Publication Date: 2022-03-15
BEIJING UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these models perform poorly in the face of two types of tasks (revaluation task, emergency change task) for evaluating brain-inspired models, i.e., the adaptability and robustness of the models become weaker in complex environments.

Method used

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  • Improved hippocampus-forehead cortex network space cognition method
  • Improved hippocampus-forehead cortex network space cognition method
  • Improved hippocampus-forehead cortex network space cognition method

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Embodiment Construction

[0059] figure 1 For the structure diagram of the model system, see figure 1 Inspired by the research of brain science and spatial cognition, the present invention provides an improved hippocampus-prefrontal cortex network spatial cognition model. The model mainly involves two brain regions, the hippocampus and the prefrontal cortex. The hippocampus receives environmental information to generate a cognitive map. The prefrontal cortex, as a supplement to the hippocampal position coding, is suitable for target representation and reward-dependent navigation planning. It is divided into dorsal cortex , ventromedial cortex, orbitofrontal cortex three sub-regions. The dorsal cortex, the ventromedial cortex, is involved in detecting changes in the environment and relaying information to the hippocampal circuit and other areas of the prefrontal cortex to support path-based planning, and the hippocampus processes this information and passes it on to the orbitofrontal cortex to set subg...

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Abstract

The invention discloses an improved hippocampus-forehead cortex network space cognition method, which comprises the following steps: firstly, a robot explores an environment to collect information, and hippocampus position cells receive the environment information and form a class topology cognition map; cortical column neurons in the forehead cortex receive and integrate hippocampus information projection and environmental award stimulation signals to evaluate the class topology cognitive map, in the evaluation process, if the robot detects that the environment is dynamically changed, the emergency change module is excited, and if multiple targets exist in the environment, the award re-estimation module is excited; finally, stimulating signals are diffused in the model in the form of neural activity waves, after evaluation is completed, reward stimulating signals are diffused in the forehead cortex network, synaptic connection between cortical column neurons in the forehead cortex is changed according to an STDP rule, and a global vector field is formed; and finally, target-oriented space navigation of the robot is realized.

Description

technical field [0001] The invention belongs to the field of bionics technology and artificial intelligence, and in particular relates to a mobile robot spatial cognition navigation model based on the hippocampus-prefrontal cortex when the environment changes. Background technique [0002] In recent years, drawing lessons from the basic principles of brain information processing, developing brain-inspired algorithms and developing brain-like intelligent systems are important areas of artificial intelligence and robotics research. It is one of the popular research directions to construct a cognitive model that imitates the mechanism of multiple brain areas of animals working together and copy it on the robot body, which is widely used in the fields of spatial cognition navigation and outdoor automatic driving in unknown environments. [0003] Spatial cognitive navigation relies on a tightly connected network of structures, including the hippocampus, prefrontal cortex, and oth...

Claims

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Application Information

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IPC IPC(8): G06N3/06G06N3/04G06N3/08
CPCG06N3/061G06N3/049G06N3/084G06N3/045
Inventor 黄静杨贺源阮晓钢于乃功任星河
Owner BEIJING UNIV OF TECH
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