Agent-Based Simulation for Cooperative Energy Policy Design: Notes from a Case Study in Apulia (Italy)

Sustainable energy transitions require coordinating heterogeneous stakeholders—developers, landowners, public institutions, and civil society— each with partial knowledge and conflicting objectives. This paper presents an agent-based decision support system (DSS) integrating ontological knowledge structuring, multi-agent simulation, and LLM-mediated reasoning. The ontology organizes the domain into four interdependent dimensions—economic, institutional, environmental, and social—providing the formal backbone for simulation variables. The system operates as a design space explorer rather than a predictive tool. An exploratory application to renewable energy localization in Apulia illustrates how the DSS supports trade-off analysis across development, regulation, and social acceptance under conditions of uncertainty.