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  • 标题:Finding Strategyproof Social Choice Functions via SAT Solving
  • 本地全文:下载
  • 作者:Felix Brandt ; Christian Geist
  • 期刊名称:Journal of Artificial Intelligence Research
  • 印刷版ISSN:1076-9757
  • 出版年度:2016
  • 卷号:55
  • 页码:565-602
  • 出版社:American Association of Artificial
  • 摘要:A promising direction in computational social choice is to address research problems using computer-aided proving techniques. In particular with SAT solvers, this approach has been shown to be viable not only for proving classic impossibility theorems such as Arrow's Theorem but also for finding new impossibilities in the context of preference extensions. In this paper, we demonstrate that these computer-aided techniques can also be applied to improve our understanding of strategyproof irresolute social choice functions. These functions, however, requires a more evolved encoding as otherwise the search space rapidly becomes much too large. Our contribution is two-fold: We present an efficient encoding for translating such problems to SAT and leverage this encoding to prove new results about strategyproofness with respect to Kelly's and Fishburn's preference extensions. For example, we show that no Pareto-optimal majoritarian social choice function satisfies Fishburn-strategyproofness. Furthermore, we explain how human-readable proofs of such results can be extracted from minimal unsatisfiable cores of the corresponding SAT formulas.
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