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What is DRL and Game Theory in Air Defense about?

This research article presents a novel decision-making framework for air defense operations that integrates deep reinforcement learning (DRL) with potential game theory. The proposed method addresses challenges such as weak interpretability and high computational demands of traditional DRL approaches by transforming target assignment into a potential game, ensuring theoretical convergence to Nash equilibrium solutions. Simulation results demonstrate that this integrated approach significantly enhances decis

Author

atinchowdhury5

Language

EN