Tsetsos Konstantinos, Moran Rani, Moreland James, Chater Nick, Usher Marius, Summerfield Christopher
Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom; Department of Psychological Sciences, Birkbeck, University of London, London WC1E 7HX, United Kingdom;
School of Psychology, University of Tel Aviv, Tel Aviv 69978, Israel; Sagol School of Neuroscience, University of Tel Aviv, Tel Aviv 69978, Israel;
Proc Natl Acad Sci U S A. 2016 Mar 15;113(11):3102-7. doi: 10.1073/pnas.1519157113. Epub 2016 Feb 29.
According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a "selective integration" policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against "late" noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.
根据规范理论,追求奖励最大化的主体应该具有一致的偏好。因此,当面对A、B和C三个选项时,一个人若偏好A甚于B,偏好B甚于C,那么他应该偏好A甚于C。然而,尽管存在强大的进化压力促使做出追求奖励最大化的选择,但人们普遍认为,人类可能会因违反这种传递性公理而遭受损失。在这里,我们采用一个具有生物学合理性的计算框架,表明当决策形成受到内部神经噪声干扰时,非传递性(因此在经济上不合理)的选择反而能提高准确性(以及随后的经济回报)。在三个实验中,我们表明人类随着时间的推移使用一种“选择性整合”策略来积累证据,该策略会丢弃关于当前价值较低选项的信息。当三个价值相等的选项在获胜样本数量上呈循环差异时,这种策略预测会违反传递性公理。我们在第四个实验中证实了这一预测,该实验报告了人类观察者中存在对弱随机传递性的显著违反。至关重要的是,我们表明依赖选择性整合可以保护选择免受“后期”噪声的影响,否则这种噪声会在感觉阶段之后破坏决策形成。事实上,我们报告说,后期噪声较高的个体更强烈地依赖选择性整合。这些发现表明,对理性选择理论的违反反映了在神经信息处理过程中为应对不可减少的噪声而进化出的适应性计算。