SEGUE: Bridging Symbolic Coordination and Embodied Execution for Sequential Social Dilemmas

Long-horizon coordination in embodied shared-resource environments requires agents to follow collective strategies while adapting to local observations, execution constraints, and failures. Symbolic solvers such as Value-Set Iteration (VSI) can compute effective high-level coordination policies, but their abstract models do not specify how recommendations should be grounded under changing embodied conditions. We propose SEGUE (Symbolic-to-Embodied Guidance for Uncertain Execution), which treats private VSI recommendations as revisable guidance and grounds action type and quantity in each agent's current context. We further introduce ESD-Bench, a closed-loop benchmark that evaluates the full symbolic-to-embodied process from recommendation and program generation to execution and resource transition. In free-action evaluation, SEGUE achieves welfare of $8.80$ versus $8.20$ for the strongest baseline in the Balanced setting, achieves the best observed welfare of $5.80$ under Scarcity, and executes $100\%$ of requested actions and quantities in both settings. It also matches symbolic VSI welfare under aligned dynamics and maintains $100\%$ joint feasibility under action-set perturbations. Ablations show that the gains stem from current coordination guidance rather than additional context or a particular backbone.