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Symbolic Noise Detection in the Noisy Iterated Chicken Game and the Noisy Iterated Battle of the Sexes

机译:嘈杂迭代鸡游戏中的象征性噪声检测和嘈杂的性别战斗

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Symbolic noise detection (SND) has been shown to be highly effective in the Noisy Iterated Prisoner's Dilemma, in which an action can accidentally be changed into a different action. This paper evaluates this technique in two other 2 × 2 repeated games: the Noisy Iterated Chicken Game (ICG) and the Noisy Iterated Battle of the Sexes (IBS). We present a generalization of SND that can be wrapped around any existing strategy. To test its performance, we organized ICG and IBS tournaments in which we solicited several dozen strategies from different authors, and we tested these strategies with and without our SND wrapper. In our tests, SND identified and corrected noise with 71% accuracy in the ICG, and 59% accuracy in the IBS. We believe the reason why SND was less effective in the ICG was because of a tendency for IBS strategies to change more frequently from one pattern of interactions to another, causing SND to make a higher number of wrong corrections. This leads us to believe that SND will be more effective in any game in which strategies often show a stable behavior.
机译:符号噪声检测(SND)已被证明在嘈杂的迭代囚犯的困境中是非常有效的,其中动作可能意外地变为不同的行动。本文评估了另外两次2×2重复游戏的这种技术:嘈杂的迭代鸡游戏(ICG)和嘈杂的迭代性(IBS)。我们展示了可以围绕任何现有策略包裹的SND的概括。为了测试其表现,我们组织了ICG和IBS锦标赛,我们从不同作者征集了几十几个策略,我们通过我们的SND包装器测试了这些策略。在我们的测试中,SND在ICG中识别和校正噪声,在ICG中具有71%的精度,在IBS中具有59%的精度。我们相信SND在ICG效果效率不太有效的原因是因为IBS策略更频繁地从另一个相互作用模式变化,导致SND制造更高数量的错误校正。这导致我们相信SND在任何战略往往表现出稳定行为的游戏中都会更有效。

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