An adaptive and robust biological network based on the vacant-particle transportation model

Gunji, Yukio Pegio; Shirakawa, Tomohiro; Niizato, Takayuki; Yamachiyo, Masaki; Tani, Iori

doi:10.1016/j.jtbi.2010.12.013

Cited by 52 publications

(41 citation statements)

References 47 publications

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“…This is time consuming. Cellular automaton models of the slime mould's foraging behaviour were proposed in [60,61]. Cellular automata are efficient in term of spatial and temporal complexity: the number of cell/node state are finite, typically less than a dozen, and size of a lattice usually does not exceed 500×500.…”

Section: Discussionmentioning

confidence: 99%

A Physarum-inspired approach to supply chain network design

Adamatzky

Yang

et al. 2016

Sci. China Inf. Sci.

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A supply chain is a system which moves products from a supplier to customers, which plays a very important role in all economic activities. This paper proposes a novel algorithm for a supply chain network design inspired by biological principles of nutrients' distribution in protoplasmic networks of slime mould Physarum polycephalum. The algorithm handles supply networks where capacity investments and product flows are decision variables, and the networks are required to satisfy product demands. Two features of the slime mould are adopted in our algorithm. The first is the continuity of flux during the iterative process, which is used in realtime updating of the costs associated with the supply links. The second feature is adaptivity. The supply chain can converge to an equilibrium state when costs are changed. Numerical examples are provided to illustrate the practicality and flexibility of the proposed method algorithm.

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Section: Discussionmentioning

confidence: 99%

A Physarum-inspired approach to supply chain network design

Adamatzky

Yang

et al. 2016

Sci. China Inf. Sci.

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“…The different modeling approaches have, also, various implementations, from the purely spatial CA models to mathematical representations of flux canalization, oscillatory behavior, two-variable Oregonator model of Belousov-Zhabotinsky (BZ) medium, and path length as found in literature [16][17][18][20][21][22][23][24][25][26][27].…”

Section: Cellular Automata Basicsmentioning

confidence: 99%

A Cellular Automata Bioinspired Algorithm Designing Data Trees in Wireless Sensor Networks

Tsompanas

Mayne

Adamatzky

2015

International Journal of Distributed Sensor Networks

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Several studies present methods to economize energy in wireless sensor networks (WSNs) which is one of the most confining resources in these systems. This paper presents a bioinspired, cellular automata (CA) based model for constructing data trees that connect all nodes with a sink node. Nonetheless, the proposed model takes into consideration not only the proximity between two nodes but also their remaining available energy. Consequently, by avoiding nodes with nearly depleted energy sources, the life time of the network can be prolonged. The plasmodium of Physarum polycephalum is the inspiration for the proposed model, as it has proved its robustness in graphically expressed problems. Moreover, CAs are able to encapsulate the parallel dynamics of the model and, thus, achieve a very fast execution.

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“…In Adamatzky's model, the wavefront is used to simulate the motion of Physarum, whose trajectory is steered by the gradient of chemo-attractants. Gunji et al have proposed a CELL model with bubbles invading to approximate the construction of Physarum networks and the solution to a maze problem (Gunji et al 2008(Gunji et al , 2011. Moreover, other researchers have developed a cellular automata based on CELL to model the behaviors of Physarum (Tsompanas and Sirakoulis 2012;Liu et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

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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.Keywords Physarum Polycephalum Á Multi-agent system Á Self-organized computational system Á Maze

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An adaptive and robust biological network based on the vacant-particle transportation model

Cited by 52 publications

References 47 publications

A Physarum-inspired approach to supply chain network design

A Physarum-inspired approach to supply chain network design

A Cellular Automata Bioinspired Algorithm Designing Data Trees in Wireless Sensor Networks

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

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