Auxiliando os Agentes de Software a Selecionar Melhor seus Parceiros
Resumo
Este trabalho propõe três mecanismos capazes de (i) ajudar um agente a identificar como outro agente avalia o comportamento de seus parceiros; (ii) estimar o valor da reputação que o agente usando a abordagem provavelmente irá receber depois de interagir com o avaliador e; (iii) calcular a reputação final do agente unindo a reputação como provedor de serviço e a reputação que o agente ao usar o mecanismo receberá se interagir com tal agente.Referências
Brase, C.H. and Brase, C.P. (2012) Understanding Basic Statistics, Brooks Cole, 6th Edition.
Bordini, R. and Hubner, J. and Wooldridge, M. (2007) Programming Multi-agent Systems in Agentspeak using Jason. John Wiley & Sons, vol. 01. p. 273, 2007.
Huynh, T. D., Jennings, N. R., Shadbolt, N. R. (2004) FIRE: An Integrated Trust and Reputation Model for Open Multi-Agent Systems, In Proceeding of ECAI, pp.18–22.
Liu, Y. and Sun, Y. (2010) Anomaly Detection in Feedback-based Reputation Systems through Temporal and Correlation Analysis, in Proc. of 2nd IEEE International Conference on Social Computing.
Liu, S et al. (2011) iCLUB: An Integrated Clustering-based Approach to Improve the Robustness of Reputation Systems. In Proceedings of International Conference on Autonomous Agents and Multi-Agent Systems, vol 3, pp. 1151–1152.
Medic, A. Survey of Computer Trust and Reputation Models – The literature Overview. (2012) International Journal of Information and Communication Technology Research, vol. 2, no 3, pp. 254-275.
Noorian, Z. and Marsh, S. and Fleming, M. (2011) Multi-layer Cognitive Filtering by Behavioral Modeling, in Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 871–878.
Silva, V; Hermoso, R.; Centeno, R. (2009) A Hybrid Reputation Model Based on the Use of Organization, In Coordination Organization, Interaction and Norms III, LNAI 5428.
Yang, Y et al. (2009) Defending Online Reputation Systems against Collaborative Unfair Raters through Signal Modeling and Trust. In Proceedings Annual Symposium on Applied Computing, Honolulu, ACM Press, pp. 1308–1315.
Zhang, J. and Cohen, R. (2008) Evaluating the Trustworthiness of Advice about Seller Agents in E-Marketplaces: A Personalized Approach. Electronic Commerce Research and Applications, 7(3), pp. 330–340.
Bordini, R. and Hubner, J. and Wooldridge, M. (2007) Programming Multi-agent Systems in Agentspeak using Jason. John Wiley & Sons, vol. 01. p. 273, 2007.
Huynh, T. D., Jennings, N. R., Shadbolt, N. R. (2004) FIRE: An Integrated Trust and Reputation Model for Open Multi-Agent Systems, In Proceeding of ECAI, pp.18–22.
Liu, Y. and Sun, Y. (2010) Anomaly Detection in Feedback-based Reputation Systems through Temporal and Correlation Analysis, in Proc. of 2nd IEEE International Conference on Social Computing.
Liu, S et al. (2011) iCLUB: An Integrated Clustering-based Approach to Improve the Robustness of Reputation Systems. In Proceedings of International Conference on Autonomous Agents and Multi-Agent Systems, vol 3, pp. 1151–1152.
Medic, A. Survey of Computer Trust and Reputation Models – The literature Overview. (2012) International Journal of Information and Communication Technology Research, vol. 2, no 3, pp. 254-275.
Noorian, Z. and Marsh, S. and Fleming, M. (2011) Multi-layer Cognitive Filtering by Behavioral Modeling, in Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 871–878.
Silva, V; Hermoso, R.; Centeno, R. (2009) A Hybrid Reputation Model Based on the Use of Organization, In Coordination Organization, Interaction and Norms III, LNAI 5428.
Yang, Y et al. (2009) Defending Online Reputation Systems against Collaborative Unfair Raters through Signal Modeling and Trust. In Proceedings Annual Symposium on Applied Computing, Honolulu, ACM Press, pp. 1308–1315.
Zhang, J. and Cohen, R. (2008) Evaluating the Trustworthiness of Advice about Seller Agents in E-Marketplaces: A Personalized Approach. Electronic Commerce Research and Applications, 7(3), pp. 330–340.
Publicado
28/05/2014
Como Citar
SARAIVA, Elane Cristina da R. C.; SILVA, Viviane Torres da.
Auxiliando os Agentes de Software a Selecionar Melhor seus Parceiros. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 8. , 2014, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 37-48.
ISSN 2326-5434.
