This paper presents an agent-based simulation framework integrating the PROMETHEUS methodology with a Collective Intelligence Genome approach to model decentralized decision-making processes in rural dairy cooperatives. The proposed framework was applied to ASPAVISO, a Colombian milk producers association operating under voluntary participation and market competition conditions. The model was implemented in NetLogo through the direct translation of PROMETHEUS artifacts into computational structures, including agent roles, beliefs, desires, intentions, coordination protocols, and behavioral plans. The Collective Intelligence Genome introduced four analytical dimensions—What, Who, Why, and How—to characterize motivational drivers, coordination mechanisms, and emergent organizational dynamics. Producers autonomously decide whether to deliver milk to the cooperative or to external collectors according to economic pressure, loyalty, cognitive biases, and institutional incentives. Simulation results demonstrate the emergence of collective behavioral patterns such as loyalty reinforcement, progressive defection, production instability, and adaptive coordination without centralized control. The study contributes a traceable methodological bridge between agent-oriented software engineering and computational social simulation, offering industrial engineering researchers a structured approach for analyzing collective intelligence and organizational sustainability in socio-productive systems.