DocumentCode
3507667
Title
Swarms of Metaheuristic Agents: A Model for Collective intelligence
Author
Aydin, Mehmet E. ; Wu, Joyce ; Zhang, Liang
Author_Institution
Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
fYear
2010
fDate
4-6 Nov. 2010
Firstpage
296
Lastpage
301
Abstract
Swarm intelligence algorithms are created to build collective intelligence based on inherent properties of populations. However, this sort of problem solving approaches use collective evolution of solutions, which make up the population relied on. Therefore the collective behaviour development is omitted. This paper addresses agentification of individuals forming up swarms, populations considered in problem solving using swarm intelligence algorithms. As each agentified individual will keep its own intelligence and use it in problem solving, the swarm intelligence algorithms used will be coordinating the agents and be supporting them in diversification of the search. This paper describes a framework of swarms of metaheuristic agents for problem solving and discusses the performance of particle swarm optimisation algorithms for purpose regarding the homogeneity in agents.
Keywords
artificial intelligence; software agents; agent homogeneity; collective intelligence model; individual agentification; metaheuristic agents; swarm intelligence algorithms; collective intelligence; metaheuristic agents; particle swarm optimization; swarm intelligence;
fLanguage
English
Publisher
ieee
Conference_Titel
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2010 International Conference on
Conference_Location
Fukuoka
Print_ISBN
978-1-4244-8538-3
Electronic_ISBN
978-0-7695-4237-9
Type
conf
DOI
10.1109/3PGCIC.2010.49
Filename
5662773
Link To Document