Resource competition and intentional disruptions, grounded in rational intergroup conflict theory, play a central role in driving strategic rivalry in networked games. These mechanisms mirror real-world conflict dynamics, profoundly shaping decision-making processes and interfering with systemic stability. This study investigates the modeling and dynamics of networked evolutionary games with intergroup conflict (NEGs-IC). In the proposed framework, players are assigned a finite number of health points, which decrease when attacked–affecting both survivability and strategic interactions. Leveraging logical dynamical system modeling, we capture the co-evolution of strategies, payoffs, health points, and player actions, demonstrating that NEGs-IC can be effectively represented as a logical dynamic system. To characterize collective interest in NEGs-IC, we introduce an objective function that balances group cooperation and health point attrition. Based on this formulation, we define three evaluation criteria–optimal, suboptimal, and weak–to assess collective interest. An illustrative example is also presented to analyze network-based conflicts, offering insights into strategic behavior in adversarial environments.
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