Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 10
3013-3017

Multi-agent cooperation rescue algorithm based on influence degree and state prediction

Zheng Yanbin
Ma Guangfu
Wang Linlin
Xi Pengxue
College of Computer & Information Engineering, Henan Normal University, Xinxiang Henan 453007, China
DOI: 10.19734/j.issn.1001-3695.2018.03.0208

Abstract

Aiming at the problem of multi-agent cooperation in disaster environment, this paper proposed a multi-agent coope-ration algorithm based on influence and state prediction. Firstly, the algorithm used the influence degree function to process the information perceived by the agent based on the information requirements of the collaborative task. Secondly, it used the predictive algorithm to predict the subsequent state of the task and the behavior of the agent, and formulated a collaborative strategy based on the prediction result. Finally, the agent performing the collaborative task dynamically adjusted the collaboration strategy according to the action effect and the trigger condition. In order to verify the effectiveness of the algorithm, it built a simulation platform in Unity3D to compare the convergence rate, the number of rescuers, and the overall score of different collaborative algorithms. The results show that the algorithm has the faster convergence speed, the better number of rescuers and the higher of overall score, which can effectively guide the collaboration between agents and provide theoretical support for the development of practical rescue coordination strategies.

Foundation Support

河南省基础前沿资助项目(142300410349)
河南省软科学资助项目(14240041001)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.03.0208
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 10
Section: Algorithm Research & Explore
Pages: 3013-3017
Serial Number: 1001-3695(2019)10-030-3013-05

Publish History

[2019-10-05] Printed Article

Cite This Article

郑延斌, 马光富, 王林林, 等. 基于影响度及状态预测的多agent协作算法 [J]. 计算机应用研究, 2019, 36 (10): 3013-3017. (Zheng Yanbin, Ma Guangfu, Wang Linlin, et al. Multi-agent cooperation rescue algorithm based on influence degree and state prediction [J]. Application Research of Computers, 2019, 36 (10): 3013-3017. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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