Fairness-Aware Static Task Assignment: Toward Ethical Resource Allocation in Multi-Agent Systems

Traditional task allocation systems aim to maximize efficiency (e.g. minimize cost or com-
pletion time) but often ignore fairness in workload distribution. This can lead to ethical issues
such as agent overburdening or uneven reward sharing. In this project, we study fairness-aware
static task assignment by augmenting a basic cost matrix with a fairness regularizer based on
Jain’s index. Unlike dynamic agent-based simulations, we consider a static setup where tasks
are distributed among agents at once. We aim to evaluate trade offs between overall efficiency
and equity across different levels of fairness regularization.