Two refined OCO algorithms with DRFM-specific unbiased gradient estimators achieve improved regret bounds and outperform standard OCO and RL baselines in anti-jamming simulations with faster convergence.
Deep q-network based anti-jamming strategy design for frequency agile radar
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Learning an Opponent-aware Anti-jamming Strategy via Online Convex Optimization
Two refined OCO algorithms with DRFM-specific unbiased gradient estimators achieve improved regret bounds and outperform standard OCO and RL baselines in anti-jamming simulations with faster convergence.