Proceedings of the Annual Meeting of the Cognitive Science Society

Which information is worth considering depends on how much effort it would take to acquire and process it. Fromthis perspective peoples tendency to neglect considering the long-term consequences of their actions (present bias) mightreflect that looking further into the future becomes increasingly more effortful. In this work, we introduce and validatethe use of Bayesian Inverse Reinforcement Learning (BIRL) for measuring individual differences in the subjective costsof planning. We extend the resource-rational model of human planning introduced by Callaway, Lieder, et al. (2018) byparameterizing the cost of planning. Using BIRL, we show that increased subjective cost for considering future outcomesmay be associated with both the present bias and acting without planning. Our results highlight testing the causal effectsof the cost of planning on both present bias and mental effort avoidance as a promising direction for future work.