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<p>Understanding conflict dynamics is crucial for developing resilient strategies in modern warfare, particularly in prolonged conflicts like the Russia–Ukraine war. While existing models often oversimplify adaptation mechanisms, our study introduces a novel adaptive agent-based framework that explicitly models real-time tactical evolution and feedback-driven strategy adaptation by both attackers and defenders in response to shifting battlefield conditions. By incorporating real-time tactical adaptation and attrition dynamics, the framework simulates interactions between attackers targeting infrastructure and defenders conducting repairs, with success probabilities determined by fixed parameters. Agents evolve their tactics based on historical outcomes and environmental feedback. Simulation results highlight three key findings: (1) defenders’ coordinated repair efforts probabilistically sustain infrastructure functionality; (2) attackers gradually degrade systems by exhausting redundancy and exploiting weak points; and (3) economic losses accelerate nonlinearly as cumulative damage increases. Crucially, over extended periods, the side that adapts more rapidly to evolving conditions maintains higher infrastructure resilience, gaining a sustained strategic advantage. This framework provides a generalizable tool for evaluating adaptive strategies, generating novel insights for policymakers on infrastructure resilience and protection strategies through scenario testing.</p>

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Simulating adaptive warfare: insights from the Russia–Ukraine conflict

  • 期刊论文

  • 发表日期：

    2026年2月17日

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  • Kishore Dutta

摘要

Understanding conflict dynamics is crucial for developing resilient strategies in modern warfare, particularly in prolonged conflicts like the Russia–Ukraine war. While existing models often oversimplify adaptation mechanisms, our study introduces a novel adaptive agent-based framework that explicitly models real-time tactical evolution and feedback-driven strategy adaptation by both attackers and defenders in response to shifting battlefield conditions. By incorporating real-time tactical adaptation and attrition dynamics, the framework simulates interactions between attackers targeting infrastructure and defenders conducting repairs, with success probabilities determined by fixed parameters. Agents evolve their tactics based on historical outcomes and environmental feedback. Simulation results highlight three key findings: (1) defenders’ coordinated repair efforts probabilistically sustain infrastructure functionality; (2) attackers gradually degrade systems by exhausting redundancy and exploiting weak points; and (3) economic losses accelerate nonlinearly as cumulative damage increases. Crucially, over extended periods, the side that adapts more rapidly to evolving conditions maintains higher infrastructure resilience, gaining a sustained strategic advantage. This framework provides a generalizable tool for evaluating adaptive strategies, generating novel insights for policymakers on infrastructure resilience and protection strategies through scenario testing.