Planning is useful. It lets people take actions that have desirable long-term
consequences. But, planning is hard. It requires thinking about consequences,
which consumes limited computational and cognitive resources. Thus, people
should plan their actions, but they should also be smart about how they deploy
resources used for planning their actions. Put another way, people should also
"plan their plans". Here, we formulate this aspect of planning as a
meta-reasoning problem and formalize it in terms of a recursive Bellman
objective that incorporates both task rewards and information-theoretic
planning costs. Our account makes quantitative predictions about how people
should plan and meta-plan as a function of the overall structure of a task,
which we test in two experiments with human participants. We find that people's
reaction times reflect a planned use of information processing, consistent with
our account. This formulation of planning to plan provides new insight into the
function of hierarchical planning, state abstraction, and cognitive control in
both humans and machines.

通过两个实验，本文将计划的计划表述为元推理问题，并用一个递归贝尔曼目标来形式化计划。 我们的研究成果在规划、状态抽象和认知控制方面提供了新的见解。