A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to model information processing within the brain. Many theorists have noted that this research seems to be in tension with a large body of experimental results purportedly documenting systematic deviations from Bayesian updating in human belief formation. In response, proponents of the Bayesian brain hypothesis contend that Bayesian models can accommodate such results by making suitable assumptions about model parameters (for example, priors, likelihoods, and utility functions). To make progress in this debate, I argue that it is fruitful to focus not on specific experimental results but rather on what I call the ‘sources of epistemic irrationality’ in human cognition. I identify four such sources and I explore whether and, if so, how Bayesian models can be reconciled with them: (1) processing costs, (2) evolutionary suboptimality, (3) motivated cognition, and (4) error management.1. Introduction2. The Bayesian Brain3. The Problem of Epistemic Irrationality3.1. Bayesian inference and rationality3.2. Intuitive Bayesian inference4. Sources of Epistemic Irrationality4.1. Processing costs4.2. Evolutionary suboptimality4.3. Motivational influences4.4. Error management5. Conclusion

中文翻译：

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贝叶斯大脑中的认知非理性

认知心理学和神经科学领域的大量研究利用贝叶斯统计来模拟大脑内的信息处理。许多理论家指出，这项研究似乎与大量实验结果存在紧张关系，这些实验结果据称记录了人类信念形成中贝叶斯更新的系统偏差。作为回应，贝叶斯大脑假设的支持者认为，贝叶斯模型可以通过对模型参数（例如，先验、似然和效用函数）做出适当的假设来适应此类结果。为了在这场辩论中取得进展，我认为不关注具体的实验结果，而是关注我所谓的人类认知中的“认知非理性的来源”是富有成效的。我确定了四个这样的来源，并探讨是否，如果是，1.引言2.贝叶斯大脑3.认知非理性问题3.1. 贝叶斯推理和合理性3.2。直观的贝叶斯推理4.认知非理性的来源4.1。处理费用4.2。进化次优4.3。动机影响4.4。错误管理5.结论