Computing Joint Action Costs: Co-Actors Minimize the Aggregate Individual Costs in an Action Sequence

Area of Science:

• Cognitive Science
• Behavioral Economics
• Computational Neuroscience

Background:

• Cooperative task performance depends on efficient task distribution.
• Individuals often sacrifice personal efficiency for joint-cost minimization (co-efficiency).

Purpose of the Study:

• Investigate the cost computations underlying co-efficient decision-making in cooperative actions.
• Test the hypothesis that joint costs are computed by summing individual action costs.

Main Methods:

• Conducted a series of experiments manipulating individual and joint action costs.
• Utilized Bayesian logistic regression models to analyze decision-making data.
• Compared model fits to evaluate the summation hypothesis.

Main Results:

• Confirmed that individuals compute joint action costs by summing their own and their co-actor's individual costs.
• Demonstrated that participants actively minimize aggregate costs to achieve co-efficiency.
• Showed that own and partner's costs are weighed similarly in joint cost estimation.

Conclusions:

• Provides empirical support for formalizing cooperation as joint utility maximization.
• Highlights the role of weighted sums of individual action costs in cooperative decision-making.
• Advances understanding of the cognitive mechanisms driving efficient cooperation.