Trust Computing Based on Argumentation Debates with Votes for Detecting Lying Agents
Resumo
Em um sistema multi-agente (SMA), é muito comum que os agentes deleguem tarefas uns aos outros. Contudo, devido à subjetividade das informações utilizadas pelos agentes durante o processo de tomada de decisão, um agente pode acabar delegando uma tarefa a um parceiro não confiável. Neste trabalho, apresentamos uma abordagem de cálculo de confiança baseada em argumentação quantitativa com votação (QuAD-V), onde a confiança é estimada de acordo com a opinião dos agentes sobre o serviço prestado por um parceiro. Além disso, tal abordagem fornece um mecanismo para avaliar a credibilidade dos agentes que atuam como fontes de informação. Como resultado, demonstramos como nossa abordagem de cálculo de confiança pode ser empregada para detectar agentes mentirosos capazes de caluniar ou promover outros agentes.
Referências
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Baroni, P., Romano, M., Toni, F., Aurisicchio, M., and Bertanza, G. (2015). Automatic evaluation of design alternatives with quantitative argumentation. Argument & Computation, 6(1):24–49.
Braga, D. D. S., Niemann, M., Hellingrath, B., and Neto, F. B. D. L. (2018). Survey on computational trust and reputation models. ACM Computing Surveys (CSUR), 51(5):1– 40.
Buccafurri, F., Comi, A., Lax, G., and Rosaci, D. (2015). Experimenting with certified reputation in a competitive multi-agent scenario. IEEE Intelligent Systems, 31(1):48– 55.
Castelfranchi, C. and Falcone, R. (1998). Towards a theory of delegation for agent-based systems. Robotics and Autonomous systems, 24(3-4):141–157.
Castelfranchi, C. and Falcone, R. (2010). Trust theory: A socio-cognitive and computational model, volume 18. John Wiley & Sons.
Castelfranchi, C. and Guerini, M. (2007). Is it a promise or a threat? Pragmatics & Cognition, 15(2):277–311.
Cayrol, C. and Lagasquie-Schiex, M.-C. (2005). On the acceptability of arguments in bipolar argumentation frameworks. In European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, pages 378–389. Springer.
Cho, J.-H., Chan, K., and Adali, S. (2015). A survey on trust modeling. ACM Computing Surveys (CSUR), 48(2):1–40.
Conte, R. and Paolucci, M. (2002). Reputation in artificial societies: Social beliefs for social order, volume 6. Springer Science & Business Media.
Conte, R. and Paolucci, M. (2003). Social cognitive factors of unfair ratings in reputation reporting systems. In Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003), pages 316–322. IEEE.
Dung, P. M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial intelligence, 77(2):321–357.
Griffiths, N. (2005). Task delegation using experience-based multi-dimensional trust. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, pages 489–496.
Kunz, W. and Rittel, H. W. (1970). Issues as elements of information systems, volume 131. Citeseer.
Miceli, M. and Castelfranchi, C. (2000). The role of evaluation in cognition and social interaction. Human cognition and agent technology, pages 225–262.
Pinyol, I. and Sabater-Mir, J. (2013). Computational trust and reputation models for open multi-agent systems: a review. Artificial Intelligence Review, 40(1):1–25.
Rago, A. and Toni, F. (2017). Quantitative argumentation debates with votes for opinIn International Conference on Principles and Practice of Multi-Agent ion polling. Systems, pages 369–385. Springer.
Rago, A., Toni, F., Aurisicchio, M., and Baroni, P. (2016). Discontinuity-free decision support with quantitative argumentation debates. In Fifteenth International Conference on the Principles of Knowledge Representation and Reasoning.
Sabater, J., Paolucci, M., and Conte, R. (2006). Repage: Reputation and image among limited autonomous partners. Journal of artificial societies and social simulation, 9(2).
Sabater, J. and Sierra, C. (2001). Regret: reputation in gregarious societies. In Proceedings of the fifth international conference on Autonomous agents, pages 194–195.
Singh, R. R. (2018). Designing for multi-agent collaboration: a shared mental model perspective. PhD thesis.
Solhaug, B., Elgesem, D., and Stolen, K. (2007). Why trust is not proportional to In The Second International Conference on Availability, Reliability and Securisk. rity (ARES’07), pages 11–18. IEEE.
Baroni, P., Romano, M., Toni, F., Aurisicchio, M., and Bertanza, G. (2015). Automatic evaluation of design alternatives with quantitative argumentation. Argument & Computation, 6(1):24–49.
Braga, D. D. S., Niemann, M., Hellingrath, B., and Neto, F. B. D. L. (2018). Survey on computational trust and reputation models. ACM Computing Surveys (CSUR), 51(5):1– 40.
Buccafurri, F., Comi, A., Lax, G., and Rosaci, D. (2015). Experimenting with certified reputation in a competitive multi-agent scenario. IEEE Intelligent Systems, 31(1):48– 55.
Castelfranchi, C. and Falcone, R. (1998). Towards a theory of delegation for agent-based systems. Robotics and Autonomous systems, 24(3-4):141–157.
Castelfranchi, C. and Falcone, R. (2010). Trust theory: A socio-cognitive and computational model, volume 18. John Wiley & Sons.
Castelfranchi, C. and Guerini, M. (2007). Is it a promise or a threat? Pragmatics & Cognition, 15(2):277–311.
Cayrol, C. and Lagasquie-Schiex, M.-C. (2005). On the acceptability of arguments in bipolar argumentation frameworks. In European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, pages 378–389. Springer.
Cho, J.-H., Chan, K., and Adali, S. (2015). A survey on trust modeling. ACM Computing Surveys (CSUR), 48(2):1–40.
Conte, R. and Paolucci, M. (2002). Reputation in artificial societies: Social beliefs for social order, volume 6. Springer Science & Business Media.
Conte, R. and Paolucci, M. (2003). Social cognitive factors of unfair ratings in reputation reporting systems. In Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003), pages 316–322. IEEE.
Dung, P. M. (1995). On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial intelligence, 77(2):321–357.
Griffiths, N. (2005). Task delegation using experience-based multi-dimensional trust. In Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, pages 489–496.
Kunz, W. and Rittel, H. W. (1970). Issues as elements of information systems, volume 131. Citeseer.
Miceli, M. and Castelfranchi, C. (2000). The role of evaluation in cognition and social interaction. Human cognition and agent technology, pages 225–262.
Pinyol, I. and Sabater-Mir, J. (2013). Computational trust and reputation models for open multi-agent systems: a review. Artificial Intelligence Review, 40(1):1–25.
Rago, A. and Toni, F. (2017). Quantitative argumentation debates with votes for opinIn International Conference on Principles and Practice of Multi-Agent ion polling. Systems, pages 369–385. Springer.
Rago, A., Toni, F., Aurisicchio, M., and Baroni, P. (2016). Discontinuity-free decision support with quantitative argumentation debates. In Fifteenth International Conference on the Principles of Knowledge Representation and Reasoning.
Sabater, J., Paolucci, M., and Conte, R. (2006). Repage: Reputation and image among limited autonomous partners. Journal of artificial societies and social simulation, 9(2).
Sabater, J. and Sierra, C. (2001). Regret: reputation in gregarious societies. In Proceedings of the fifth international conference on Autonomous agents, pages 194–195.
Singh, R. R. (2018). Designing for multi-agent collaboration: a shared mental model perspective. PhD thesis.
Solhaug, B., Elgesem, D., and Stolen, K. (2007). Why trust is not proportional to In The Second International Conference on Availability, Reliability and Securisk. rity (ARES’07), pages 11–18. IEEE.
Publicado
29/11/2021
Como Citar
BAQUETA, Jeferson José; MORVELI-ESPINOZA, Mariela; TACLA, Cesar A..
Trust Computing Based on Argumentation Debates with Votes for Detecting Lying Agents. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 410-421.
ISSN 2763-9061.
DOI: https://doi.org/10.5753/eniac.2021.18271.
