SafeAgentGrid: A Hierarchical Constitutional Multi-Agent Framework for Trustworthy Autonomous Resource Optimization in Smart Energy Infrastructures

<jats:p>Autonomous multi-agent reinforcement learning (MARL) has been increasingly entrusted with real-time control of smart energy infrastructures, where agents remain vulnerable to the false data injection attacks (FDIA), Byzantine failures, and specification misalignment. Existing proposed constitutional AI techniques target discrete language-based coordination and offer no protection for continuous-action cyber-physical control. In this paper, we propose SafeAgentGrid, a hierarchical neuro-symbolic constitutional framework integrating (1) constitutional agents whose actions pass a projection filter that can guarantee every hard box-type constraint by the construction; (2) a hybrid neural-surrogate mediator whose low-latency fast path has been admitted only after a split-conformal test bounding its alignment shortfall, and whose full path resolves a constrained program over a tightened DC reachable set, fairness (Gini) and risk-aware security weighting; and (3) 8-bit quantized models for edge computing. On a DC power-flow simulation with a ring-topology susceptance matrix (10 agents, 40 evaluation episodes), the proposed SafeAgentGrid accomplishes 200,186.9 average reward, 0.0125 ± 0.0014 violations/step (0.0194 ± 0.0016 under 20% FDIA; 0.0140 ± 0.0015 under the Byzantine failure of \( \lfloor N/3\rfloor \) agents), 100% grid efficiency, 0.999 alignment and 0.92 ms/step latency, outperforming four strong related techniques, trained in the same environment, in both reward and safety (Wilcoxon signed-rank, p ≤ 3.4 × 10-8). We further show that tightening the reachable set is really necessary for the safety guarantee in order to survive stochastic realization, that robust repair must be anchored on a per-agent physical reference rather than the population median, and that the effectiveness of the security module is governed by the weight with which the mediator delegates authority to the agents.</jats:p>