Particle swarm social model for group social learning in adaptive environment

Xiaohui Cui; Laura L. Pullum; Jim Treadwell; Robert M. Patton; Thomas E. Potok

doi:10.1007/978-0-387-77672-9_16

Particle swarm social model for group social learning in adaptive environment

Xiaohui Cui, Laura L. Pullum, Jim Treadwell, Robert M. Patton, Thomas E. Potok

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

This report presents a study of integrating particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the social learning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provides a platform for understanding and insights into knowledge discovery and strategic search in human self-organized social groups, such as human communities.

Original language	English
Title of host publication	Social Computing, Behavioral Modeling, and Prediction, 2008
Editors	John J. Salerno, Michael J. Young, Huan Liu
Publisher	Springer
Pages	141-150
Number of pages	10
ISBN (Print)	9780387776712
DOIs	https://doi.org/10.1007/978-0-387-77672-9_16
State	Published - 2008
Event	1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008 - Phoenix, United States Duration: Apr 1 2008 → Apr 2 2008

Publication series

Name	Social Computing, Behavioral Modeling, and Prediction, 2008

Conference

Conference	1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008
Country/Territory	United States
City	Phoenix
Period	04/1/08 → 04/2/08

Funding

Acknowledgements Prepared by Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725; and by Lockheed Martin, partially funded by internal Lockheed research funds.

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10.1007/978-0-387-77672-9_16

Cite this

Cui, X., Pullum, L. L., Treadwell, J., Patton, R. M., & Potok, T. E. (2008). Particle swarm social model for group social learning in adaptive environment. In J. J. Salerno, M. J. Young, & H. Liu (Eds.), Social Computing, Behavioral Modeling, and Prediction, 2008 (pp. 141-150). (Social Computing, Behavioral Modeling, and Prediction, 2008). Springer. https://doi.org/10.1007/978-0-387-77672-9_16

@inproceedings{be045faf2efc454aae42cfb5796950ec,

title = "Particle swarm social model for group social learning in adaptive environment",

abstract = "This report presents a study of integrating particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the social learning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provides a platform for understanding and insights into knowledge discovery and strategic search in human self-organized social groups, such as human communities.",

author = "Xiaohui Cui and Pullum, {Laura L.} and Jim Treadwell and Patton, {Robert M.} and Potok, {Thomas E.}",

note = "Publisher Copyright: {\textcopyright} 2008 Springer Science+Business Media, LLC.; 1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008 ; Conference date: 01-04-2008 Through 02-04-2008",

year = "2008",

doi = "10.1007/978-0-387-77672-9_16",

language = "English",

isbn = "9780387776712",

series = "Social Computing, Behavioral Modeling, and Prediction, 2008",

publisher = "Springer",

pages = "141--150",

editor = "Salerno, {John J.} and Young, {Michael J.} and Huan Liu",

booktitle = "Social Computing, Behavioral Modeling, and Prediction, 2008",

}

Cui, X, Pullum, LL, Treadwell, J , Patton, RM & Potok, TE 2008, Particle swarm social model for group social learning in adaptive environment. in JJ Salerno, MJ Young & H Liu (eds), Social Computing, Behavioral Modeling, and Prediction, 2008. Social Computing, Behavioral Modeling, and Prediction, 2008, Springer, pp. 141-150, 1st International workshop on Social Computing, Behavioral Modeling and Prediction, 2008, Phoenix, United States, 04/1/08. https://doi.org/10.1007/978-0-387-77672-9_16

Particle swarm social model for group social learning in adaptive environment. / Cui, Xiaohui; Pullum, Laura L.; Treadwell, Jim et al.
Social Computing, Behavioral Modeling, and Prediction, 2008. ed. / John J. Salerno; Michael J. Young; Huan Liu. Springer, 2008. p. 141-150 (Social Computing, Behavioral Modeling, and Prediction, 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Patton, Robert M.

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PY - 2008

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N2 - This report presents a study of integrating particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the social learning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provides a platform for understanding and insights into knowledge discovery and strategic search in human self-organized social groups, such as human communities.

AB - This report presents a study of integrating particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the social learning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provides a platform for understanding and insights into knowledge discovery and strategic search in human self-organized social groups, such as human communities.

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BT - Social Computing, Behavioral Modeling, and Prediction, 2008

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Y2 - 1 April 2008 through 2 April 2008

ER -

Particle swarm social model for group social learning in adaptive environment

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