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Consensus effects in categorization decisions

机译:分类决策中的共识效应

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A previous study (Gilat et al., J. Exp. Psychol. Appl. 3 (1997) 83) has shown that the incentive to reach consensus can raise the tendency to rely on base rates in signal detection decisions and can reduce the probability that less likely events will be accurately classified. This phenomenon was named the "consensus effect". The current study assesses the conditions under which this effect develops and in particular the effects of information about the game and of the incentive structure on the learning process. The results of three experiments show that the learning process slows when participants have information about the actual state of nature. This finding is captured by a reinforcement learning model with the assumption that information narrows the distribution of the initial propensities for choosing among cutoffs. The results are further evidence for the utility of the combination of learning models and analyses of cognitive processes for the prediction of decision making in situations involving multiple players.
机译:先前的研究(Gilat等人,J。Exp。Psychol。Appl。3(1997)83)显示,达成共识的动机可以提高信号检测决策中依赖基本速率的趋势,并可以降低不太可能发生的事件将被准确分类。这种现象被称为“共识效应”。当前的研究评估了这种影响发展的条件,尤其是有关游戏信息和激励结构对学习过程的影响。三个实验的结果表明,当参与者获得有关自然状态的信息时,学习过程会变慢。这一发现是通过强化学习模型来捕获的,该模型的前提是信息会缩小用于在临界值之间进行选择的初始倾向的分布。这些结果进一步证明了学习模型和认知过程分析相结合对于在涉及多个参与者的情况下进行决策预测的效用。

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