Use of deep reinforcement learning (Double DQN-C51) for mobility optimization in wireless sensor networks to generate fairly accurate maps on a tracked phenomenon modeled by a Gaussian Process.
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Use of deep reinforcement learning (Double DQN-C51) for mobility optimization in wireless sensor networks to generate fairly accurate maps on a tracked phenomenon modeled by a Gaussian Process
sami15as42/Reinforcement-Learning-for-MIPP
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Use of deep reinforcement learning (Double DQN-C51) for mobility optimization in wireless sensor networks to generate fairly accurate maps on a tracked phenomenon modeled by a Gaussian Process
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