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Fairness-Aware Static Task Assignment: Toward Ethical Resource Allocation in Multi-Agent Systems
Abdullah Naveed • Nadia Farokhpay
abstract
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.
