Successful cooperative activities rely on the efficient distribution of sub-tasks between co-actors. Previous research has found that people often forgo individual efficiency in favor of group-level efficiency (i.e., joint cost minimization) when planning a joint action. The present study investigated the cost computations underlying such "co-efficient" decisions: We tested the hypothesis that people compute the joint costs of a shared action sequence by summing the individual costs of their own and their co-actor's actions. We independently manipulated the parameters quantifying individual and joint action costs and tested their effects on decision-making. Participants weighed their own and their partner's costs equally to estimate the joint action costs as the sum of the two individual parameters. The results provide empirical support for computational approaches that formalize cooperation as joint utility maximization based on a sum of individual action costs.
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