Abstract
The traditional Cellular Automation-based Physarum model reveals the process of amoebic self-organized movement and self-adaptive network formation based on bubble transportation. However, a bubble in the traditional Physarum model often transports within active zones and has little change to explore new areas. And the efficiency of evolution is very low because there is only one bubble in the system. This paper proposes an improved model, named as Improved Bubble Transportation Model (IBTM). Our model adds a time label for each grid of environment in order to drive bubbles to explore new areas, and deploys multiple bubbles in order to improve the evolving efficiency of Physarum network. We first evaluate the morphological characteristics of IBTM with the real Physarum, and then compare the evolving time between the traditional model and IBTM. The results show that IBTM can obtain higher efficiency and stability in the process of forming an adaptive network.
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Liu, Y., Zhang, Z., Gao, C., Wu, Y., Qian, T. (2013). A Physarum Network Evolution Model Based on IBTM. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_3
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DOI: https://doi.org/10.1007/978-3-642-38715-9_3
Publisher Name: Springer, Berlin, Heidelberg
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