Norms in human societies are expectations of behaviours of the individuals. In human societies, there are several types of norms such as moral norms, social norms and legal norms (laws). In multi-agent systems, software agents are modelled as possessing characteristics and behaviour borrowed from human societies. In order to design and develop robust artificial agent societies, it is important to understand different approaches proposed by researchers by which norms can spread and emerge within agent societies. This paper makes three contributions to the study of norms. Firstly, based on the simulation research on norms, we propose a life-cycle model for norms. Secondly, we discuss different mechanisms used by researchers to study norm creation, identification, spreading, enforcement and emergence. We also discuss the strengths and weaknesses of each of these mechanisms. Thirdly, in the context of identifying the desired characteristics of the simulation models of norms we discuss the research issues that need to be addressed.
%0 Journal Article
%1 savarimuthu2011creation
%A Savarimuthu, Bastin Tony Roy
%A Cranefield, Stephen
%D 2011
%J Multiagent and Grid Systems
%K agents myown
%N 1
%P 21-54
%T Norm creation, spreading and emergence: A survey of simulation models of norms in multi-agent systems
%U http://dx.doi.org/10.3233/MGS-2011-0167
%V 7
%X Norms in human societies are expectations of behaviours of the individuals. In human societies, there are several types of norms such as moral norms, social norms and legal norms (laws). In multi-agent systems, software agents are modelled as possessing characteristics and behaviour borrowed from human societies. In order to design and develop robust artificial agent societies, it is important to understand different approaches proposed by researchers by which norms can spread and emerge within agent societies. This paper makes three contributions to the study of norms. Firstly, based on the simulation research on norms, we propose a life-cycle model for norms. Secondly, we discuss different mechanisms used by researchers to study norm creation, identification, spreading, enforcement and emergence. We also discuss the strengths and weaknesses of each of these mechanisms. Thirdly, in the context of identifying the desired characteristics of the simulation models of norms we discuss the research issues that need to be addressed.
@article{savarimuthu2011creation,
abstract = {Norms in human societies are expectations of behaviours of the individuals. In human societies, there are several types of norms such as moral norms, social norms and legal norms (laws). In multi-agent systems, software agents are modelled as possessing characteristics and behaviour borrowed from human societies. In order to design and develop robust artificial agent societies, it is important to understand different approaches proposed by researchers by which norms can spread and emerge within agent societies. This paper makes three contributions to the study of norms. Firstly, based on the simulation research on norms, we propose a life-cycle model for norms. Secondly, we discuss different mechanisms used by researchers to study norm creation, identification, spreading, enforcement and emergence. We also discuss the strengths and weaknesses of each of these mechanisms. Thirdly, in the context of identifying the desired characteristics of the simulation models of norms we discuss the research issues that need to be addressed.},
added-at = {2011-09-29T03:43:33.000+0200},
author = {Savarimuthu, Bastin Tony Roy and Cranefield, Stephen},
biburl = {https://www.bibsonomy.org/bibtex/23eb319c19afd9207fcb3509f79fcf6e2/scranefield},
interhash = {aa29610ce762fe0f073ae628fc1fbeb3},
intrahash = {3eb319c19afd9207fcb3509f79fcf6e2},
journal = {Multiagent and Grid Systems},
keywords = {agents myown},
number = 1,
pages = {21-54},
timestamp = {2012-10-18T01:38:55.000+0200},
title = {Norm creation, spreading and emergence: A survey of simulation models of norms in multi-agent systems},
url = {http://dx.doi.org/10.3233/MGS-2011-0167},
volume = 7,
year = 2011
}