Time-inconsistency is a characteristic of human behavior in which people plan for long-term benefits but take actions that differ from the plan due to conflicts with short-term benefits. Such time-inconsistent behavior is believed to be caused by present bias, a tendency to overestimate immediate rewards and underestimate future rewards. It is essential in behavioral economics to investigate the relationship between present bias and time-inconsistency. In this paper, we propose a model for analyzing agent behavior with present bias in tasks to make progress toward a goal over a specific period. Unlike previous models, the state sequence of the agent can be described analytically in our model. Based on this property, we analyze three crucial problems related to agents under present bias: task abandonment, optimal goal setting, and optimal reward scheduling. Extensive analysis reveals how present bias affects the condition under which task abandonment occurs and optimal intervention strategies. Our findings are meaningful for preventing task abandonment and intervening through incentives in the real world.

翻译：时间不一致性是人类行为的一个特征，即人们为长期利益制定计划，但由于与短期利益的冲突而采取与计划不同的行动。这种时间不一致行为被认为是由现时偏好引起的，即高估即时回报而低估未来回报的倾向。在行为经济学中，研究现时偏好与时间不一致性之间的关系至关重要。本文提出一个模型，用于分析具有现时偏好的智能体在特定时期内朝着目标前进的任务中的行为。与以往模型不同，在我们的模型中，智能体的状态序列可以解析描述。基于这一特性，我们分析了与具有现时偏好的智能体相关的三个关键问题：任务放弃、最优目标设定和最优奖励调度。广泛分析揭示了现时偏好如何影响任务放弃发生的条件以及最优干预策略。我们的发现对于在现实世界中通过激励措施预防任务放弃并进行干预具有意义。