How the ability to analyse tendencies influences decision satisfaction

Detalhes bibliográficos
Autor(a) principal: Carneiro, João
Data de Publicação: 2017
Outros Autores: Martinho, Diogo, Conceição, Luís, Marreiros, Goreti, Novais, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/1822/50520
Resumo: Using agents to represent decision-makers is a complex task. It is important that agents can understand the context and be more proactive. Here we propose a model and an algorithm that will allow the agent to analyse tendencies regarding the number of supporters for each alternative along the process. It is intended that agents can be more dynamic and intelligent and can evaluate different contexts throughout the decision-making process. We believe agents will achieve better and consensual decisions more easily. We tested our model in three simulation environments with different complexity levels. Our model proved that agents that use it will obtain higher average consensus and satisfaction levels. Besides that, agents using this model will obtain those higher consensus and satisfaction levels in most of the times compared to agents that do not use it.
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spelling How the ability to analyse tendencies influences decision satisfactionGroup Decision Support SystemsArgumentationDecision SatisfactionAutomatic NegotiationMulti-Agent SystemsEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaUsing agents to represent decision-makers is a complex task. It is important that agents can understand the context and be more proactive. Here we propose a model and an algorithm that will allow the agent to analyse tendencies regarding the number of supporters for each alternative along the process. It is intended that agents can be more dynamic and intelligent and can evaluate different contexts throughout the decision-making process. We believe agents will achieve better and consensual decisions more easily. We tested our model in three simulation environments with different complexity levels. Our model proved that agents that use it will obtain higher average consensus and satisfaction levels. Besides that, agents using this model will obtain those higher consensus and satisfaction levels in most of the times compared to agents that do not use it.This work is part-funded by ERDF- European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEISII/1386/2012) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Project UID/CEC/00319/2013 and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersionSociedad Iberoamericana de Inteligencia Artificial (IBERAMIA)Universidade do MinhoCarneiro, JoãoMartinho, DiogoConceição, LuísMarreiros, GoretiNovais, Paulo2017-022017-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/50520engCarneiro J., Martinho D., Conceição L., Mareiros G., Novais P., How the ability to analyse tendencies influences decision satisfaction, Inteligencia Artificial, Vol. 20, nº 59, ISSN 1137-3601, pp 8-20, 2017. https://doi.org/10.4114/intartif.vol20iss59pp8-20.1137-36011988-306410.4114/intartif.vol20iss59pp8-20http://journal.iberamia.org/index.php/intartif/article/view/80info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T04:37:07Zoai:repositorium.sdum.uminho.pt:1822/50520Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:53:30.542114Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv How the ability to analyse tendencies influences decision satisfaction
title How the ability to analyse tendencies influences decision satisfaction
spellingShingle How the ability to analyse tendencies influences decision satisfaction
Carneiro, João
Group Decision Support Systems
Argumentation
Decision Satisfaction
Automatic Negotiation
Multi-Agent Systems
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short How the ability to analyse tendencies influences decision satisfaction
title_full How the ability to analyse tendencies influences decision satisfaction
title_fullStr How the ability to analyse tendencies influences decision satisfaction
title_full_unstemmed How the ability to analyse tendencies influences decision satisfaction
title_sort How the ability to analyse tendencies influences decision satisfaction
author Carneiro, João
author_facet Carneiro, João
Martinho, Diogo
Conceição, Luís
Marreiros, Goreti
Novais, Paulo
author_role author
author2 Martinho, Diogo
Conceição, Luís
Marreiros, Goreti
Novais, Paulo
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Carneiro, João
Martinho, Diogo
Conceição, Luís
Marreiros, Goreti
Novais, Paulo
dc.subject.por.fl_str_mv Group Decision Support Systems
Argumentation
Decision Satisfaction
Automatic Negotiation
Multi-Agent Systems
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Group Decision Support Systems
Argumentation
Decision Satisfaction
Automatic Negotiation
Multi-Agent Systems
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description Using agents to represent decision-makers is a complex task. It is important that agents can understand the context and be more proactive. Here we propose a model and an algorithm that will allow the agent to analyse tendencies regarding the number of supporters for each alternative along the process. It is intended that agents can be more dynamic and intelligent and can evaluate different contexts throughout the decision-making process. We believe agents will achieve better and consensual decisions more easily. We tested our model in three simulation environments with different complexity levels. Our model proved that agents that use it will obtain higher average consensus and satisfaction levels. Besides that, agents using this model will obtain those higher consensus and satisfaction levels in most of the times compared to agents that do not use it.
publishDate 2017
dc.date.none.fl_str_mv 2017-02
2017-02-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/50520
url http://hdl.handle.net/1822/50520
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carneiro J., Martinho D., Conceição L., Mareiros G., Novais P., How the ability to analyse tendencies influences decision satisfaction, Inteligencia Artificial, Vol. 20, nº 59, ISSN 1137-3601, pp 8-20, 2017. https://doi.org/10.4114/intartif.vol20iss59pp8-20.
1137-3601
1988-3064
10.4114/intartif.vol20iss59pp8-20
http://journal.iberamia.org/index.php/intartif/article/view/80
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA)
publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial (IBERAMIA)
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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