2013 IEEE 16th International Conference on Computational Science and Engineering (2009)
Aug. 29, 2009 to Aug. 31, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSE.2009.209
Many evidence-based trust models require the adjustment of parameters such as aging- or exploration-factors. What the literature often does not address is the systematic choice of these parameters. In our work, we propose a generic procedure for finding trust model parameters that maximize the expected utility to the trust model user. The procedure is based on gametheoretic considerations and uses a genetic algorithm to cope with the vast number of possible attack strategies. To demonstrate the feasibility of the approach, we apply our procedure to a concrete trust model and optimize the parameters of this model.
Trust, Parameterization, Genetic Algorithm, Game Theory, Benchmarking
T. Engel and E. Staab, "Tuning Evidence-Based Trust Models," 2009 International Conference on Computational Science and Engineering(CSE), Vancouver, Canada, 2009, pp. 92-99.