Vol.5 No.10 (October 2015)
The Neural Learning Mechanism of the Gambler’s Fallacy Bias in Random Sequences Generation
朱 滢 ：北京大学心理学系，北京
The gambler’s bias refers to the preference for alteration patterns when people generate random sequences. That is, for example, when tossing fair coins, if one side appears, people would prefer to anticipate the other side to be more possible to appear next. The gambler’s bias is generally thought to be human brain’s misperception of random sequences which results from the repre-sentativeness bias. However, Sun et al. (2015) uncovered the latent structure in random sequen- ces, and provided a neural learning mechanism for the gambler’s bias using this statistical struc-ture. This finding not only gives a rational explanation for the bias but also provides a mathematical description for the cognitive processing of uncertainty and randomness in human mind.
过继成思 , 朱 滢 (2015) 随机序列生成中赌徒谬误的神经学习机制。 心理学进展， 5， 604-608. doi: 10.12677/AP.2015.510078
Falk, R., & Konold, C. (1997). Making sense of randomness: Implicit encoding as a basis for judgment. Psychological Review, 104, 301-318.
Goodfellow, L. D. (1938). A psychological interpretation of the results of the Zenith radio experiments in telepathy. Journal of Experimental Psychology, 23, 601.
 Griffiths, T. L., & Tenenbaum, J. B. (2001). Randomness and coincidences: Reconciling intuition and probability theory. Proceedings of the 23rd Annual Conference of the Cognitive Science Society, 370-375.
Sun, Y., O’Reilly, R. C., Bhattacharyya, R., Smith, J. W., Liu, X., & Wang, H. (2015). Latent structure in random sequences drives neural learning toward a rational bias. Proceedings of the National Academy of Sciences, 112, 3788-3792.