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A Multi-agent Dynamic Task Allocation Method Based on Task Model

A multi-agent, dynamic task technology, applied in multi-programming devices, program startup/switching, distributed object-oriented systems, etc., can solve the problem of affecting task completion efficiency, wasting intelligent robot resources, and unable to meet the dynamic nature of task allocation. and real-time requirements to achieve the effect of improving completion efficiency and meeting real-time requirements

Active Publication Date: 2021-12-14
CENT SOUTH UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the current multi-agent system, the task-oriented dynamic changes, the current algorithm has some shortcomings, not only will cause a waste of agent robot resources, but also cannot meet the dynamic and real-time requirements of task allocation, seriously affecting the efficiency of task completion

Method used

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  • A Multi-agent Dynamic Task Allocation Method Based on Task Model
  • A Multi-agent Dynamic Task Allocation Method Based on Task Model
  • A Multi-agent Dynamic Task Allocation Method Based on Task Model

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Embodiment Construction

[0084] The present invention will be described in detail below according to the accompanying drawings, which is a preferred embodiment among various implementations of the present invention.

[0085] In a preferred embodiment, a task model-based multi-agent dynamic task allocation method, the present invention proposes a task model dynamic task allocation method to solve the problem of multiple dynamic tasks in the environment through cooperation among agents.

[0086] The dynamic task allocation method adopts the following steps: obtain the information of the environment, analyze its information, and quickly deploy the agents in the environment initially. The agents go to their respective target points to perform tasks according to the initial deployment plan. The agents in the environment maintain Communicate, share information in real time, and perform dynamic fine-tuning at regular intervals so that the overall task completion time is close. When all tasks are executed, the...

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Abstract

The invention provides a multi-agent dynamic task allocation method based on a task model, which mainly solves the problem of multi-task allocation in which task state quantities have time-varying characteristics. Including: first obtain the state information of the task in the environment, and combine the agent's ability parameters to establish a task state quantity model; secondly, quickly deploy the initial agent, and the agent communicates with other agents in the environment during the execution process and shares them in real time Information, so as to dynamically fine-tune the agent and cooperate to complete all tasks. The task allocation method proposed by the present invention aims to complete all tasks as quickly as possible, and realizes rapid dynamic task allocation. Through multi-stage dynamic fine-tuning, it can fully mobilize the intelligent agents in the system to perform tasks cooperatively, and improve the overall execution effect of the system.

Description

technical field [0001] The invention relates to the technical field of real-time assignment of multi-agent system tasks, and more specifically, relates to a multi-agent dynamic task assignment method based on a task model. Background technique [0002] Multi-agent system is one of the problems that people are generally concerned about in recent years. As an important branch of distributed artificial intelligence, multi-agent system has autonomy, distribution, coordination, and self-learning ability, organizational ability and reasoning ability. , providing a new solution to complex real-world problems; multi-agents can replace humans to help us complete certain tasks in some harsh environments, and are widely used in industry, national defense, exploration and disaster relief and other fields, while in multi-agent systems In the research of the multi-agent task allocation problem occupies an important basic position. [0003] In the current multi-agent system, the oriented ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/48G06F9/46
CPCG06F9/465G06F9/4881
Inventor 陈杰裘智峰郭宇骞杨宁管建锋桂卫华
Owner CENT SOUTH UNIV
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