Abstract:Multi-task learning provides plenty of room for performance improvement to single-task learning, when learned tasks are related and learned with mutual information. In this work, we analyze the efficiency of using a single-task reinforcement learning algorithm to mitigate jamming attacks with frequency hopping strategy. Our findings show that single-task learning implementations do not always guarantee optimal cumulative reward when some jammer's parameters are unknown, notably the jamming time-slot length in … Show more
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