Selective Sampling with Information-Storage Constraints
研究无记忆的决策者如何通过选择性丢弃信号来控制行动与状态的相关性，推导出最优停止条件，并解释了确认偏误、速度-准确性互补、罕见事件高估和显著性效应。
Abstract A memoryless agent can acquire arbitrarily many signals. After each signal observation, she either terminates and chooses an action, or she discards her observation and draws a new signal. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the benefits of selective memory applied to the extracted signals. Implications—obtained in simple examples—include (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.