A new multi-agent system to simulate the foraging behaviors of Physarum

Liu, Yuxin, Gao, Chao, Zhang, Zili, Wu, Yuheng, Liang, Mingxin, Tao, Li and Lu, Yuxiao 2017, A new multi-agent system to simulate the foraging behaviors of Physarum, Natural computing, vol. 16, no. 1, pp. 15-29, doi: 10.1007/s11047-015-9530-5.

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Title A new multi-agent system to simulate the foraging behaviors of Physarum
Formatted title A new multi-agent system to simulate the foraging behaviors of Physarum
Author(s) Liu, Yuxin
Gao, Chao
Zhang, ZiliORCID iD for Zhang, Zili orcid.org/0000-0002-8721-9333
Wu, Yuheng
Liang, Mingxin
Tao, Li
Lu, Yuxiao
Journal name Natural computing
Volume number 16
Issue number 1
Start page 15
End page 29
Total pages 15
Publisher Springer
Place of publication Dordrecht, The Netherlands
Publication date 2017-03
ISSN 1567-7818
Keyword(s) Physarum polycephalum
Multi-agent system
Self-organised computational system
Summary Physarum Polycephalum is a unicellular and multi-headed slime mold, which can form high efficient networks connecting spatially separated food sources in the process of foraging. Such adaptive networks exhibit a unique characteristic in which network length and fault tolerance are appropriately balanced. Based on the biological observations, the foraging process of Physarum demonstrates two self-organized behaviors, i.e., search and contraction. In this paper, these two behaviors are captured in a multi-agent system. Two types of agents and three transition rules are designed to imitate the search and the contraction behaviors of Physarum based on the necessary and the sufficient conditions of a self-organized computational system. Some simulations of foraging process are used to investigate the characteristics of our system. Experimental results show that our system can autonomously search for food sources and then converge to a stable solution, which replicates the foraging process of Physarum. Specially, a case study of maze problem is used to estimate the path-finding ability of the foraging behaviors of Physarum. What’s more, the model inspired by the foraging behaviors of Physarum is proposed to optimize meta-heuristic algorithms for solving optimization problems. Through comparing the optimized algorithms and the corresponding traditional algorithms, we have found that the optimization strategies have a higher computational performance than their corresponding traditional algorithms, which further justifies that the foraging behaviors of Physarum have a higher computational ability.
Language eng
DOI 10.1007/s11047-015-9530-5
Field of Research 080503 Networking and Communications
0801 Artificial Intelligence And Image Processing
0803 Computer Software
080503 Networking and Communications
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Springer Science+Business Media Dordrecht
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082159

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