Understanding of Complex Adaptive Systems (CAS) is challenging due to their emergent and adaptive properties. We propose a framework to identify stable strategies and potential system outcomes in CAS by focusing on key interactions between stakeholders. In our framework, CAS is modeled as multi-agent systems and surrogate modeling with game-theoretic concepts are used to extract a game that captures strategic behaviors, i.e., decisions taken by stakeholders that influence both their own and others’ outcomes. We illustrate the practical relevance of our framework in the domain of urban logistics, more specifically in a mutualization use case where decision-making by shippers, freight carriers, and urban consolidation centers shapes the overall dynamics of the system.