文献类型：期刊文献

英文题名：Behavioral modeling with the new bio-inspired coordination generalized molecule model algorithm

作者：Feng, Xiang[1];Lau, Francis C. M.[2];Yu, Huiqun[1]

机构：[1]E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China;[2]Univ Hong Kong, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China

年份：2013

卷号：252

起止页码：1

外文期刊名：INFORMATION SCIENCES

收录：;EI(收录号：20133916770807);WOS:【SCI-EXPANDED(收录号:WOS:000325674000001)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 60905043, 61073107 and 61173048, the General Research Fund of Hong Kong Research Grant Council under Grant No. 7137/08E, the Innovation Program of Shanghai Municipal Education Commission, and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Social networks (SN); Social behavior; Social coordination; Coordination generalized molecule model (CGMM)

摘要：Social Networks (SN) is an increasingly popular topic in artificial intelligence research. One of the key directions is to model and study the behaviors of social agents. In this paper, we propose a new computational model which can serve as a powerful tool for the analysis of SN. Specifically, we add to the traditional sociometric methods a novel analytical method in order to deal with social behaviors more effectively, and then present a new bio-inspired model, the coordination generalized molecule model (CGMM). The proposed analytical method for social behaviors and CGMM are combined to give an algorithm that can be used to solve complex problems in SN. Traditionally, SN models were mainly descriptive and were built at a very coarse level, typically with only a few global parameters, and turned out to be not sufficiently useful for analyzing social behaviors. In this work, we explore bio-inspired analytical models for analyzing social behaviors of intelligent agents. Our objective is to propose an effective and practical method to model intelligent systems and their behaviors in an open and complex unpredictable world. (c) 2011 Elsevier Inc. All rights reserved.