Learning under unawareness
研究了在可以进行实验但存在无意识和模糊性的情况下，个体如何学习。模型将完全缺乏信息表达为先验族，随着信息积累，意识状态空间可能扩展，新状态起初模糊但逐渐清晰。
Abstract We propose a model of learning when experimentation is possible, but unawareness and ambiguity matter. In this model, complete lack of information regarding the underlying data generating process is expressed as a (maximal) family of priors. These priors yield posterior inferences that become more precise as more information becomes available. As information accumulates, however, the individual’s level of awareness as encoded in the state space may expand. Such newly learned states are initially seen as ambiguous, but as evidence accumulates there is a gradual reduction of ambiguity.