When deciding how to act under uncertainty, agents may choose to act to reduce uncertainty or they may act despite that uncertainty. In communicative settings, an important way of reducing uncertainty is by asking clarification questions (CQs). We predict that the decision to ask a CQ depends on both contextual uncertainty and the cost of alternative actions, and that these factors interact: uncertainty should matter most when acting incorrectly is costly. We formalize this interaction in a computational model based on expected regret: how much an agent stands to lose by acting now rather than with full information. We test these predictions in two experiments, one examining purely linguistic responses to questions and another extending to choices between clarification and non-linguistic action. Taken together, our results suggest a rational tradeoff: humans tend to seek clarification proportional to the risk of substantial loss when acting under uncertainty.

翻译：在不确定性条件下决定如何行动时，智能体可选择采取行动以降低不确定性，也可能在不确定状态下直接行动。在沟通情境中，提出澄清性问题（CQs）是降低不确定性的重要方式。我们预测，提出澄清性问题的决策既取决于情境不确定性，也取决于替代行动的成本，且这两个因素存在交互作用：当错误行动代价高昂时，不确定性因素将产生最大影响。我们基于预期遗憾（即智能体在当前信息不全时行动相较于掌握完整信息时行动可能遭受的损失）构建了描述这种交互作用的计算模型。通过两项实验验证上述预测：第一项实验考察纯语言层面的问题回应行为，第二项实验扩展至澄清性提问与非语言行动之间的选择。综合结果表明存在理性权衡机制：人类在不确定性条件下行动时，倾向于根据可能遭受重大损失的风险程度按比例寻求澄清。