{"title":"Social identity theory applied to the game of self-regulation of social exchanges based on multiagent systems","authors":"Jader Saldanha, D. Adamatti, G. Dimuro","doi":"10.1080/17477778.2021.1977730","DOIUrl":null,"url":null,"abstract":"ABSTRACT Autonomous intelligent agents participate in complex social situations. It is necessary that agents are aware of their society and still understand their context of action and interaction. Such social situation with other agents is influenced by society’s characteristics, including their norms, values, common interests and objectives, members, and social structures. Each complex society is broken down into social groups, each one with an identity. Social identity theory is seen as an analysis of intergroup relations in social categories based on the cognitive definition and the autoconcept of a social group and their belonging. Researchers have been studying this theory in computing, more specifically in multiagent systems. Social exchanges are the object of study in diverse contexts in which social relations are understood as social exchanges. One of the investigated themes is the self-regulation of social exchanges. The game of self-regulation of social exchanges explores its self-regulation but it does not analyse the agents’ identity. Therefore, this research investigates the integration of psychosocial analysis of social identity theory into the social adaptive complex society of the game of self-regulation of social exchanges. The principal result of this work is the GSRSEPSIT, a social simulation model.","PeriodicalId":51296,"journal":{"name":"Journal of Simulation","volume":"17 1","pages":"164 - 177"},"PeriodicalIF":1.3000,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Simulation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/17477778.2021.1977730","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT Autonomous intelligent agents participate in complex social situations. It is necessary that agents are aware of their society and still understand their context of action and interaction. Such social situation with other agents is influenced by society’s characteristics, including their norms, values, common interests and objectives, members, and social structures. Each complex society is broken down into social groups, each one with an identity. Social identity theory is seen as an analysis of intergroup relations in social categories based on the cognitive definition and the autoconcept of a social group and their belonging. Researchers have been studying this theory in computing, more specifically in multiagent systems. Social exchanges are the object of study in diverse contexts in which social relations are understood as social exchanges. One of the investigated themes is the self-regulation of social exchanges. The game of self-regulation of social exchanges explores its self-regulation but it does not analyse the agents’ identity. Therefore, this research investigates the integration of psychosocial analysis of social identity theory into the social adaptive complex society of the game of self-regulation of social exchanges. The principal result of this work is the GSRSEPSIT, a social simulation model.
Journal of SimulationCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.70
自引率
16.00%
发文量
42
期刊介绍:
Journal of Simulation (JOS) aims to publish both articles and technical notes from researchers and practitioners active in the field of simulation. In JOS, the field of simulation includes the techniques, tools, methods and technologies of the application and the use of discrete-event simulation, agent-based modelling and system dynamics.