Social networks in simulated multi-robot environment

被引:10
|
作者
Rodic, Daniel [1 ]
Engelbrecht, Andries P. [1 ]
机构
[1] Univ Pretoria, Sch Informat Technol, Dept Comp Sci, Pretoria, South Africa
关键词
Coordination; Multi-robot teams; Social networks; Socio-economic models; Multi-agent systems;
D O I
10.1108/17563780810857158
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose - The purpose of this paper is to present a novel approach to coordination of multi-agent teams, and in particular multi-robot teams. The new approach is based on models of organisational sociology, namely the concept of social networks. The social relationships used in the model that is presented in this paper are trust and kinship relationships, but modified for use in heterogeneous multi-robot teams. Design/methodology/approach - The coordination of a robot team is achieved through task allocation. The proposed task allocation mechanism was tested in the multi-robot team task allocation simulation. Findings - The social networks-based task allocation algorithm has performed according to expectations and the obtained results are very promising. Some intriguing similarities with higher mammalian societies were observed and they are discussed in this paper. The social networks-based approach also exhibited the ability to learn and store information using social networks. Research limitations/implications - The research focused on simulated environments and further research is envisaged in the physical environments to confirm the applicability of the presented approach. Practical implications - In this paper, the proposed coordination was applied to simulated multi-robot teams. It is important to note that the proposed coordination model is not robot specific, but can also be applied to almost any multi-agent system without major modifications. Originality/value - The paper emphasizes applicability of considering multi-robot teams as socially embodied agents. It also presents a novel and efficient approach to task allocation.
引用
收藏
页码:110 / 127
页数:18
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