Pareto Set Identification

Pareto set identification aims to find the optimal set of solutions in multi-objective optimization problems, where no single solution dominates all others. Current research focuses on developing efficient algorithms, such as those based on empirical gap elimination or adaptive exploration strategies, to identify this set within various model frameworks, including multi-armed bandits and linear bandits, often incorporating robustness to noisy or adversarial data. These advancements are significant for diverse applications, enabling the selection of optimal strategies in scenarios with multiple competing objectives, such as resource allocation or clinical trial design, where finding a single "best" solution is insufficient.