This repository contains the data and the analysis used for the paper
"No Evidence for Cost-Benefit Arbitration Between Social Learning Strategies"
by Ariel Levy, Xavier Roberts-Gaal, and Fiery Cushman;
Proceedings of the Annual Meeting of the Cognitive Science Society, 2025
When learning a task by observing another person performing it, an individual can either focus on imitating the other’s behavior (policy imitation), or attempt to infer the other’s goals and beliefs and adjust their own behavior accordingly (goal emulation). Imitation is considered to be computationally cheap but less accurate, while emulation is considered to be computationally costly but more accurate.
Drawing upon research on computational resource rationality, we ask whether individuals incorporate cost-benefit considerations when choosing whether to imitate actions or emulate goals. To answer this question, we used an observational-learning extension of a two-step bandit task, and manipulated the reward at stake.
Participants’ behavior was best fit by a dual-process model of goal emulation and one-step imitation, consistent with findings from previous research. However, contrary to our hypothesis and inconsistent with cost-benefit arbitration, we found no evidence that rewards at stake influenced participants’ social learning strategies.