Abstract
How do noise and manipulation affect the accuracy of collective decision rules? This paper presents simulation results that measure the accuracy of ten well known collective decision rules under noise and manipulation. When noise is low these rules can be divided into accurate ("good") and inaccurate ("bad") groups. The bad rules’ accuracy improves, sometimes significantly, when noise increases while the good rules’ performance steadily worsens with noise. Also, when noise increases the accuracy of the good rules deteriorates at different rates. Manipulation delays the effects of noise: accuracy improvement and deterioration due to noise emerge only at higher noise levels with manipulation than without it. In some cases at high noise levels there is only a negligible difference between the accuracy of good and bad collective decision rules.
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Bodo, P. (2009). The Effects of Noise and Manipulation on the Accuracy of Collective Decision Rules. In: Rossi, F., Tsoukias, A. (eds) Algorithmic Decision Theory. ADT 2009. Lecture Notes in Computer Science(), vol 5783. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04428-1_6
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DOI: https://doi.org/10.1007/978-3-642-04428-1_6
Publisher Name: Springer, Berlin, Heidelberg
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