Task model-based multi-agent dynamic task allocation method

A multi-agent, dynamic task technology, applied in the direction of multi-program device, program startup/switching, distributed object-oriented system, etc., can solve the problem of affecting the efficiency of task completion, wasting intelligent robot resources, and not satisfying the dynamic nature of task assignment and real-time requirements

Active Publication Date: 2018-05-08
CENT SOUTH UNIV
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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

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  • Task model-based multi-agent dynamic task allocation method
  • Task model-based multi-agent dynamic task allocation method
  • Task model-based multi-agent dynamic task allocation method

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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, which solves 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...

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Abstract

The invention provides a task model-based multi-agent dynamic task allocation method, and mainly solves the multi-task allocation problem that a task state quantity has a time-varying characteristic.The method comprises the steps of firstly obtaining state information of tasks in an environment, and in combination with capability parameters of agents, building a task state quantity model; and secondly quickly performing initial deployment on the agents, enabling the agents to communicate with other agents in the environment during an execution process to share the information in real time, performing dynamic fine adjustment on the agents, and enabling the agents to cooperate for finishing all the tasks. According to the task allocation method provided by the invention, quick allocation ofdynamic tasks is realized by taking operation of finishing all the tasks at a highest speed as a goal; and through multi-stage dynamic fine adjustment, the agents in the system can be fully scheduledto cooperatively execute the tasks, so that the overall execution effect of the system is improved.

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 ...

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Application Information

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Patent Type & Authority Applications(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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