People are often confronted with problems whose complexity exceeds their cognitive capacities. To deal with this complexity, individuals and managers can break complex problems down into a series of subgoals. Which subgoals are most effective depends on people's cognitive constraints and the cognitive mechanisms of goal pursuit. This creates an untapped opportunity to derive practical recommendations for which subgoals managers and individuals should set from cognitive models of bounded rationality. To seize this opportunity, we apply the principle of resource-rationality to formulate a mathematically precise normative theory of (self-)management by goal-setting. We leverage this theory to computationally derive optimal subgoals from a resource-rational model of human goal pursuit. Finally, we show that the resulting subgoals improve the problem-solving performance of bounded agents and human participants. This constitutes a first step towards grounding prescriptive theories of management and practical recommendations for goal-setting in computational models of the relevant psychological processes and cognitive limitations.

翻译：人们常常面临复杂性超出其认知能力的问题。为应对这种复杂性，个体与管理者可将复杂问题分解为一系列子目标。哪些子目标最为有效，取决于人们的认知约束与目标追求的认知机制。这为从有限理性认知模型中推导出关于管理者与个体应设定何种子目标的实践建议创造了未开发的机遇。为把握这一机遇，我们应用资源理性原则，构建了一个数学上精确的（自我）管理目标设定规范理论。进而利用该理论，从人类目标追求的资源理性模型中计算推导出最优子目标。最后，我们证明所得子目标能提升有限理性智能体与人类参与者的解题能力。这标志着将管理规范理论与目标设定实践建议，奠基于相关心理过程与认知局限计算模型的第一步。