Distributed stochastic resource allocation in teams

Consideration is given to distributed dynamic resource allocation within a two-person team. Having different but overlapping responsibilities, two geographically separated human decision-makers (DMs) are to process multiple types of randomly arriving tasks with a set of renewable resources. To maximize the team reward for task processing, the DMs must coordinate on the assignment of common tasks (tasks of joint responsibility) and on the transfer of resources. A normative-descriptive approach is adopted to describe the human decision-making process in the above setting. The approach starts with a normative model that predicts the team´s optimal decision-making and a human-in-the-loop experiment that generates experimental data. Human limitations and cognitive biases are then identified to explain differences between model predictions and experimental data. Incorporating human limitations and cognitive biases into the normative model, a normative-descriptive model is obtained. This model matches experimental data in almost all measures and provides insights to human decision-making behavior