A Data-Driven Serious Game for Human-Wildlife Conflict Management in Kerala

Human-wildlife conflicts (HWC) pose a significant challenge to biodiversity conservation and sustainable livelihoods, particularly in regions where human settlements overlap with wildlife habitats. In Kerala, total of more than 450 deaths were reported in the past five years. Traditional conflict mitigation approaches often lack stakeholder engagement and fail to address the complexity of ecological and socio-economic factors. This paper proposes a novel serious game framework that employs role-playing and AI-driven decision models to simulate realworld HWC scenarios. The serious game used data collected from multiple sources, to make the simulations realistic as possible. By integrating participatory modeling, agent-based simulations, and rapid evolution, our approach enables stakeholders—including farmers, policymakers, and conservationists—to explore dynamic interactions and evaluate mitigation strategies in a risk-free environment. The proposed framework enhances adaptive decision-making, promotes stakeholder collaboration, and offers a scalable tool for conservation planning. Empirical validation through case studies demonstrates its effectiveness in fostering conflict resolution and policy experimentation. Our findings suggest that serious games can bridge the gap between theoretical conservation models and real-world decision-making by providing an interactive and cognitively engaging learning experience. Empirical validation through a case study with 50 participants demonstrated improved conflict resolution strategies and enhanced stakeholder consensus. Our findings suggest that serious games can bridge the gap between theoretical conservation models and real-world decision-making by providing an interactive and cognitively engaging learning experience.