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Title: Particle Swarm Based Collective Searching Model for Adaptive Environment

Abstract

This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.

Authors:
 [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
Work for Others (WFO)
OSTI Identifier:
986767
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Book
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; BEHAVIOR; ADAPTIVE SYSTEMS; SOCIOLOGY; INFORMATION RETRIEVAL; COMMUNICATIONS; Particle swarm; Modeling; Adaptive environment; Self-organized

Citation Formats

Cui, Xiaohui, Patton, Robert M, Potok, Thomas E, and Treadwell, Jim N. Particle Swarm Based Collective Searching Model for Adaptive Environment. United States: N. p., 2007. Web.
Cui, Xiaohui, Patton, Robert M, Potok, Thomas E, & Treadwell, Jim N. Particle Swarm Based Collective Searching Model for Adaptive Environment. United States.
Cui, Xiaohui, Patton, Robert M, Potok, Thomas E, and Treadwell, Jim N. Mon . "Particle Swarm Based Collective Searching Model for Adaptive Environment". United States. doi:.
@article{osti_986767,
title = {Particle Swarm Based Collective Searching Model for Adaptive Environment},
author = {Cui, Xiaohui and Patton, Robert M and Potok, Thomas E and Treadwell, Jim N},
abstractNote = {This report presents a pilot study of an integration of particle swarm algorithm, social knowledge adaptation and multi-agent approaches for modeling the collective search behavior of self-organized groups in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social group adaptation for the dynamic environment and to provide insight and understanding of social group knowledge discovering and strategic searching. A new adaptive environment model, which dynamically reacts to the group collective searching behaviors, is proposed in this research. The simulations in the research indicate that effective communication between groups is not the necessary requirement for whole self-organized groups to achieve the efficient collective searching behavior in the adaptive environment.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}

Book:
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