Promising and worth-to-try future directions for advancing state-of-the-art surrogates methods of agent-based models in social and health computational sciences

The PDF is an ad‑hoc perspective that lists four objectives for ABM surrogates—Accuracy, Robustness (multi‑output/time‑series), Reduction (equation‑based ML), and Reliability—and sketches candidate methods in Table 1, but it does not state precise mathematical claims or provide proofs (the text explicitly frames these as promising, worth‑to‑try directions) . The candidate solution formalizes each objective with clear assumptions and proves appropriate guarantees or counterexamples; its logic is generally sound, with only minor constant‑level tightening needed in the sub‑Gaussian vector‑norm concentration used in Task 1B/1C. The paper’s contribution is therefore incomplete (no theorems or proofs), while the model’s solution provides a rigorous instantiation aligned with the paper’s aims (including a precise reliability criterion and stability via Wasserstein‑Lipschitz analysis) .