The model of coherent lower and upper conditional previsions, based on Hausdorff inner and outer measures, is proposed to represent the preference orderings and the equivalences, respectively assigned by the conscious and unconscious thought in human decision making under uncertainty. Complexity of partial information is represented by the Hausdorff dimension of the conditioning event. When the events, that describe the decision problem, are measurable is represented to the s-dimensional Hausdorff outer measure, where s is the Hausdorff dimension of the conditioning event, an optimal decision can be reached. The model is applied and discussed in Linda’s Problem and the conjunction fallacy is resolved.

提出了基于Hausdorff内部和外部测度的上下条件前置条件的模型，以表示不确定性条件下有意识和无意识思想在人类决策中分别分配的偏好顺序和等价性。部分信息的复杂性由条件事件的Hausdorff维表示。当描述决策问题的事件是可测量的时，用s维Hausdorff外部度量表示，其中s是条件事件的Hausdorff维，则可以得出最佳决策。该模型在Linda问题中得到应用和讨论，并且合取谬误得以解决。