By Shangce Gao, Hongjian Chai, Beibei Chen, Gang Yang (auth.), Ying Tan, Yuhui Shi, Hongwei Mo (eds.)
This publication and its significant other quantity, LNCS vols. 7928 and 7929 represent the court cases of the 4th foreign convention on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised complete papers offered have been conscientiously reviewed and chosen from 268 submissions. The papers are geared up in 22 cohesive sections overlaying all significant themes of swarm intelligence learn and advancements. the subjects lined during this quantity are: hybrid algorithms, swarm-robot and multi-agent structures, help vector machines, info mining tools, method and data protection, clever keep an eye on, instant sensor community, scheduling and course making plans, photograph and video processing, and different applications.
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Additional resources for Advances in Swarm Intelligence: 4th International Conference, ICSI 2013, Harbin, China, June 12-15, 2013, Proceedings, Part II
19–26, 2013. c Springer-Verlag Berlin Heidelberg 2013 20 Y. Liu et al. based on feedback regulations between the internal protoplasmic ﬂow and the thickness of each tube. Adamatzky [10,11] has utilized an Oregonator model to simulate the growth and foraging behavior of plasmodium of Physarum. Jones [6,12] has illustrated the evolving process of Physarum-like transport networks through a bottom-up multi-agent based system. However, the aforementioned models are unable to further explain the relationship between the process of network formation and the movement of amoeba, which plays a central role in Physarum computing .
Agent I agent II agent I (a) (b) (c) agent II (d) Fig. 3. The mutually-exclusive relationship breaks oﬀ all routes connecting the leftbottom active zone when two agents transport in parallel The general idea of this strategy is as follows. First, multiple agents are randomly generated with diﬀerent positions based on “generation behavior” respectively. Second, each agent randomly chooses and transports to one adjacent internal grid that has not been resided by any agent based on the modiﬁed “movement behavior”.
1 Introduction Physarum Polycephalum is a unicellular and multi-headed slime mold which lives in a dark and moist environment. Biological experiments show that the plasmodium — a ‘vegetative’ phase of Physarum — has the ability to form self-adaptive and high eﬃcient networks without central control mechanism. Statistical analyses show that such networks have the shortest path with higher fault tolerance [1,2]. These Physarum networks are comparable to real-world infrastructure networks, such as UK motorways , the Tokyo rail system , the longest road in USA and the longest national motorway in Europe .