Modelling trust for communicating agents: agent-based and population-based perspectives
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
Modeling and Validation of Biased Human Trust
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Agent-Based and population-based modeling of trust dynamics
Transactions on Computational Collective Intelligence IX
Design and validation of a relative trust model
Knowledge-Based Systems
Modelling biased human trust dynamics
Web Intelligence and Agent Systems
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Trust dynamics can be modelled in relation to experiences. Both cognitive and neural models for trust dynamics in relation to experiences are available, but were not yet related or compared in more detail. This paper presents a comparison between a cognitive and a neural model. As each of the models has its own specific set of parameters, with values that depend on the type of person modelled, such a comparison is nontrivial. In this paper a comparison approach is presented that is based on mutual mirroring of the models in each other. More specifically, for given parameter values set for one model, by automated parameter estimation processes the most optimal values for the parameter values of the other model are determined to show the same behaviour. Roughly spoken the results are that the models can mirror each other up to an accuracy of around 90%.