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Ranking of Weighted Majority Rules
| Content Provider | Scilit |
|---|---|
| Author | Berend, Daniel Chernyavsky, Yuri Sapir, Luba |
| Copyright Year | 2008 |
| Description | A decision-making body may utilize a wide variety of different strategies when required to make a collective decision. In principle, we would like to use the most effective decision rule, that is, the rule yielding the highest probability of making the correct decision. However, in reality we often have to choose a decision rule out of some restricted family of rules. Therefore, it is important to be able to rank various families of rules. In this paper we consider three classes of decision rules: (i) balanced expert rules, (ii) the so-called single expert rules, and (iii) restricted majority rules. For the first two classes, we show that, as we deviate from the best rule in the family, the effectiveness of the decision rule decreases. For the last class, we obtain a very different phenomenon: any inner ranking is possible. |
| Related Links | https://www.cambridge.org/core/services/aop-cambridge-core/content/view/5D9ABD56BE8CD517375DCAB8AB452BB5/S0021900200004939a.pdf/div-class-title-ranking-of-weighted-majority-rules-div.pdf |
| ISSN | 00219002 |
| e-ISSN | 14756072 |
| DOI | 10.1017/s0021900200004939 |
| Journal | Journal of applied probability |
| Issue Number | 04 |
| Volume Number | 45 |
| Language | English |
| Publisher | Cambridge University Press (CUP) |
| Publisher Date | 2008-12-01 |
| Access Restriction | Open |
| Subject Keyword | Journal of applied probability Artificial Intelligence Decision Rule Weighted Majority Rule Balanced Expert Rule Restricted Majority Rule Dichotomous Choice Model |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Statistics, Probability and Uncertainty |
