GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points

Hexing Yang; Qingjie Zhao; Lei Wang; Wangwang Liu; Ling Chong

doi:10.1007/978-981-99-2789-0_12

GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points

Hexing Yang, Qingjie Zhao^*, Lei Wang, Wangwang Liu, Ling Chong

^*Corresponding author for this work

School of Computer Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Multi-agent technology is widely used in many fields such as intelligent manufacturing, logistics and environment exploration. In this paper, we propose a greedy K-means self-organizing map algorithm to balance the tasks and plan the paths for multiple agents exploring multiple target points, where greedy k-means adopts greedy strategy to ensure the tasks allocated for agents tending equally, and the self-organizing map networks are used for parallel path planning to speed up the problem solved.

Original language	English
Title of host publication	Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers
Editors	Fuchun Sun, Jianmin Li, Huaping Liu, Zhongyi Chu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	139-147
Number of pages	9
ISBN (Print)	9789819927883
DOIs	https://doi.org/10.1007/978-981-99-2789-0_12
Publication status	Published - 2023
Event	1st International Conference on Cognitive Computation and Systems, ICCCS 2022 - Beijing, China Duration: 17 Dec 2022 → 18 Dec 2022

Publication series

Name	Communications in Computer and Information Science
Volume	1732 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	1st International Conference on Cognitive Computation and Systems, ICCCS 2022
Country/Territory	China
City	Beijing
Period	17/12/22 → 18/12/22

Keywords

Greedy K-means
Multi-agent
Path planning
Self-organizing map

Access to Document

10.1007/978-981-99-2789-0_12

Cite this

Yang, H., Zhao, Q., Wang, L., Liu, W., & Chong, L. (2023). GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points. In F. Sun, J. Li, H. Liu, & Z. Chu (Eds.), Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers (pp. 139-147). (Communications in Computer and Information Science; Vol. 1732 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-2789-0_12

Yang, Hexing ; Zhao, Qingjie ; Wang, Lei et al. / GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points. Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers. editor / Fuchun Sun ; Jianmin Li ; Huaping Liu ; Zhongyi Chu. Springer Science and Business Media Deutschland GmbH, 2023. pp. 139-147 (Communications in Computer and Information Science).

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title = "GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points",

abstract = "Multi-agent technology is widely used in many fields such as intelligent manufacturing, logistics and environment exploration. In this paper, we propose a greedy K-means self-organizing map algorithm to balance the tasks and plan the paths for multiple agents exploring multiple target points, where greedy k-means adopts greedy strategy to ensure the tasks allocated for agents tending equally, and the self-organizing map networks are used for parallel path planning to speed up the problem solved.",

keywords = "Greedy K-means, Multi-agent, Path planning, Self-organizing map",

author = "Hexing Yang and Qingjie Zhao and Lei Wang and Wangwang Liu and Ling Chong",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 1st International Conference on Cognitive Computation and Systems, ICCCS 2022 ; Conference date: 17-12-2022 Through 18-12-2022",

year = "2023",

doi = "10.1007/978-981-99-2789-0_12",

language = "English",

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series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "139--147",

editor = "Fuchun Sun and Jianmin Li and Huaping Liu and Zhongyi Chu",

booktitle = "Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers",

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}

Yang, H, Zhao, Q, Wang, L, Liu, W & Chong, L 2023, GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points. in F Sun, J Li, H Liu & Z Chu (eds), Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers. Communications in Computer and Information Science, vol. 1732 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 139-147, 1st International Conference on Cognitive Computation and Systems, ICCCS 2022, Beijing, China, 17/12/22. https://doi.org/10.1007/978-981-99-2789-0_12

GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points. / Yang, Hexing; Zhao, Qingjie; Wang, Lei et al.
Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers. ed. / Fuchun Sun; Jianmin Li; Huaping Liu; Zhongyi Chu. Springer Science and Business Media Deutschland GmbH, 2023. p. 139-147 (Communications in Computer and Information Science; Vol. 1732 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points

AU - Yang, Hexing

AU - Zhao, Qingjie

AU - Wang, Lei

AU - Liu, Wangwang

AU - Chong, Ling

PY - 2023

Y1 - 2023

N2 - Multi-agent technology is widely used in many fields such as intelligent manufacturing, logistics and environment exploration. In this paper, we propose a greedy K-means self-organizing map algorithm to balance the tasks and plan the paths for multiple agents exploring multiple target points, where greedy k-means adopts greedy strategy to ensure the tasks allocated for agents tending equally, and the self-organizing map networks are used for parallel path planning to speed up the problem solved.

AB - Multi-agent technology is widely used in many fields such as intelligent manufacturing, logistics and environment exploration. In this paper, we propose a greedy K-means self-organizing map algorithm to balance the tasks and plan the paths for multiple agents exploring multiple target points, where greedy k-means adopts greedy strategy to ensure the tasks allocated for agents tending equally, and the self-organizing map networks are used for parallel path planning to speed up the problem solved.

KW - Greedy K-means

KW - Multi-agent

KW - Path planning

KW - Self-organizing map

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U2 - 10.1007/978-981-99-2789-0_12

DO - 10.1007/978-981-99-2789-0_12

M3 - Conference contribution

AN - SCOPUS:85163388333

SN - 9789819927883

T3 - Communications in Computer and Information Science

SP - 139

EP - 147

BT - Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers

A2 - Sun, Fuchun

A2 - Li, Jianmin

A2 - Liu, Huaping

A2 - Chu, Zhongyi

PB - Springer Science and Business Media Deutschland GmbH

T2 - 1st International Conference on Cognitive Computation and Systems, ICCCS 2022

Y2 - 17 December 2022 through 18 December 2022

ER -

Yang H, Zhao Q, Wang L, Liu W, Chong L. GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points. In Sun F, Li J, Liu H, Chu Z, editors, Cognitive Computation and Systems - First International Conference, ICCCS 2022, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2023. p. 139-147. (Communications in Computer and Information Science). doi: 10.1007/978-981-99-2789-0_12

GK-Means SOM Algorithm Used to Plan the Paths for Multiple Agents Exploring Multiple Target Points

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