Social Networks and Multi-agent Organizational Performance

Social Networks and Multi-agent Organizational Performance (2004)

by Matthew E. Gaston, et al.

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Datum	Value	Source
TITLE	Social Networks and Multi-agent Organizational Performance	SVM HeaderParse 0.2
AUTHOR NAME	Matthew E. Gaston, et al.	user correction
ABSTRACT	In studying the dynamical behavior of processes in artificial or natural social systems, a key factor is the topology of the network structure. It has been shown that real-world social networks tend to have non-random network structure with properties such as short average path length, excess clustering, and skewed degree distributions (Albert & Barab asi 2002; Newman 2003). We show in this paper that the nature of the network structure in a social network of artificial or simulated agents has a significant effect on the performance of the overall system. We conclude that finding "good" network structures for a particular application domain is critical to modeling artificial social systems and implementing multiagent systems. We argue that techniques for adapting network structure will be critical in large-scale agent communities.	user correction - Legacy Corrections
YEAR	2004	user correction
CITATIONS	24 found	ParsCit 1.0