[1]L IU Bai-long,ZHANG Ru-bo,SH I Chang-ting.Modeling and simulating the foraging system in multi-source groups with random disturbances[J].CAAI Transactions on Intelligent Systems,2008,3(4):342-348.
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Modeling and simulating the foraging system in multi-source groups with random disturbances

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 3 Number of periods: 2008 4 Page number: 342-348 Column: 学术论文—智能系统 Public date: 2008-08-25
Title:
Modeling and simulating the foraging system in multi-source groups with random disturbances
Author(s):
L IU Bai-long;  ZHANG Ru-bo;  SH I Chang-ting
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Keywords:
swarm intelligence;  self2organization;  foraging; modeling;  Starlogo simulation
CLC:
TP18
DOI:
-
Abstract:
Swarm intelligence ( SI) is artificial intelligence based on observable collective behavior of decentralized, self2organized systems, otherwise known as social animals, and is gaining more attention from researchers. SI sys2 tems are typ icallymade up of a population of simp le agents interacting locallywith one another and with their envi2 ronment. The agents follow very simp le rules, and although there is no centralized control structure dictating how individual agents should behave, local interactions between such agents lead to the emergence of comp lex global be2 havior. Specially, the foraging behavior of ant colonies have be viewed as a p rototyp ical examp le of how comp lex group behavior can arise from simp le individual behaviors. In order to study the feature of self2organization in SI, first a macroscop ic serial parametric model for flock foragingwas established, in which the richness and distribution of food sourceswere considered as well as the stochastic effects of a noisy environment. Numerical solutions were given for systematic modelswith two food sources. These showed that, in an environmentwith great noise, the op ti2 mal solution may not be found and a second2best solution may instead be reached. Simulations on the Starlogo p lat2 form showed a power law relationship between the number of ants and comp letion time aswell as the flux of forag2 ers. The work p resented here may imp rove the understanding of self2organization and swarm intelligence. It can al2 so be used to design more efficient, adap tive, and reliable intelligent systems
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