Decision-making Models under Present Bias in Cumulation-type Tasks

Abstract

Time-inconsistency is a characteristic of human behavior to plan for long-term benefits but to take actions that differ from the plan due to conflicts with short-term benefits. The time-inconsistent behavior is believed to be caused by present bias, a tendency to overestimate immediate rewards and underestimate future rewards. It is an essential issue in behavioral economics to investigate the relationship between the present bias and time-inconsistency.This paper proposes a new model to analyze agent behavior with present bias in tasks to make progress toward a goal over a specific period. Unlike previous models, our model has the significant feature that the state sequence of the agent can be described analytically. Based on this property, we analyze three crucial problems related to agents under present bias: task abandonment, optimal goal setting, and optimal reward scheduling. Our extensive analysis reveals the impact of present bias on time-inconsistency and optimal intervention strategies, leading to meaningful insights about intervention through incentives in the real world.