dc.creatorBraz, Luiz Fernando
dc.creatorSichman, Jaime Simão
dc.date2022-01-11
dc.date.accessioned2022-10-04T22:28:01Z
dc.date.available2022-10-04T22:28:01Z
dc.identifierhttps://seer.ufrgs.br/index.php/rita/article/view/RITA_Vol29_Nr1_42
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3870448
dc.descriptionThe formation of high-performance teams has been a constant challenge for organizations, which despite considering human capital as one of the most important resources, it still lacks the means to allow them to have a better understanding of several factors that influence the formation of these teams. In this sense, studies also demonstrate that teamwork has a significant impact on the results presented by organizations, in which human behavior is highlighted as one of the main aspects to be considered in the building of work teams. The Myers-Briggs Type Indicator seeks to classify the behavioral preferences of individuals around eight characteristics, which grouped as dichotomies, describe different psychological types. With it, researchers have sought to expand the ability to understand the human factor, using strategies with multiagent systems that, through experiments and simulations, using computer resources, enable the development of artificial agents that simulate human actions. In this work, we present an overview of the research approaches that use MBTI to model agents, aiming at providing a better knowledge of human behavior. Additionally, we make a preliminary discussion of how these results could be explored in order to advance the studies of psychological factors' influence in organizations' work teams formation.en-US
dc.formatapplication/pdf
dc.languageeng
dc.publisherInstituto de Informática - Universidade Federal do Rio Grande do Sulen-US
dc.relationhttps://seer.ufrgs.br/index.php/rita/article/view/RITA_Vol29_Nr1_42/pdf
dc.rightsCopyright (c) 2022 Luiz Fernando Braz, Jaime Simão Sichmanpt-BR
dc.sourceRevista de Informática Teórica e Aplicada; Vol. 29 No. 1 (2022); 42-53en-US
dc.sourceRevista de Informática Teórica e Aplicada; v. 29 n. 1 (2022); 42-53pt-BR
dc.source2175-2745
dc.source0103-4308
dc.subjectMultiagent systemsen-US
dc.subjectMASen-US
dc.subjectHigh-Performance Teamsen-US
dc.subjectMBTIen-US
dc.titleUsing the Myers-Briggs Type Indicator (MBTI) for Modeling Multiagent Systemsen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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