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A cargo transportation system based on multi-agent reinforcement learning

A reinforcement learning and multi-agent technology, applied in the field of multi-agent systems, can solve problems such as inability to solve convergence problems, affect system performance and efficiency, and slow down system convergence speed, so as to reduce pressure, improve efficiency, and improve performance Effect

Active Publication Date: 2022-06-21
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But in fact, in a multi-agent environment, due to differences in distance, speed and other factors, for a single freight agent, there may be some unnecessary information or even interference information in all freight agent information, and the communication information If the amount is too large, it may slow down the convergence of the system and affect the performance and efficiency of the entire system
In addition, in the current research on multi-intelligence reinforcement learning, it cannot solve the convergence problem when the number of freight agents is large.

Method used

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  • A cargo transportation system based on multi-agent reinforcement learning
  • A cargo transportation system based on multi-agent reinforcement learning
  • A cargo transportation system based on multi-agent reinforcement learning

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Embodiment Construction

[0041] In order to facilitate understanding of the present invention, the present invention will be described more fully hereinafter with reference to the related drawings. Preferred embodiments of the invention are shown in the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that a thorough and complete understanding of the present disclosure is provided.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terms used herein in the description of the present invention are for the purpose of describing specific embodiments only, and are not intended to limit the present invention.

[0043] The cargo transportation system based on multi-agent reinforcement learning provided by the present i...

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Abstract

The invention relates to a cargo transportation system based on multi-agent reinforcement learning, comprising: a freight intelligent body, a grouping module and a model building module; the grouping module is used to obtain the position coordinates of each freight intelligent body, and Algorithms group all freight agents to obtain at least one freight agent group; the model building block is used to divide the freight agents in each freight agent group through the implicit weighting algorithm, and the freight agent group in the freight agent group Implicit coordination control of multiple freight agents; use the centralized critic method of multi-agent deep deterministic policy gradient algorithm to build a neural network, and generate the optimized path of multiple freight agents through the neural network. The freight agent follows this optimized path around obstacles and reaches landmarks. The present invention can handle a large number of freight intelligent bodies with a large amount of communication information, and has good performance, high efficiency and low cost.

Description

technical field [0001] The invention belongs to the technical field of multi-agent systems, in particular to a cargo transportation system based on multi-agent reinforcement learning. Background technique [0002] With the development of artificial intelligence, communication and information technologies, the research of multi-agent has been a research hotspot of many people in recent years. Multi-agent systems can be widely used in public facility detection, disaster environmental investigation, military reconnaissance, warehouse handling and other fields, and have been widely used in both military and civilian applications. In the process of freight transportation, it is a very important problem to enable multiple freight agents to intelligently plan routes to reach multiple different locations to place goods, because this can speed up the efficiency of freight transportation and reduce labor costs. It is also increasingly becoming a focus of research. Among them, the co...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/08G06N3/04G06N3/08
CPCG06Q10/083G06Q10/0833G06Q10/08355G06N3/08G06N3/045
Inventor 姜元爽宁立张涌冯圣中
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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