Deep Reinforcement Learning by Balancing Offline Monte Carlo and Online Temporal Difference Use Based on Environment Experiences
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DOI: 10.3390/sym12101685
Abstract: Owing to the complexity involved in training an agent in a real-time environment, e.g., using the Internet of Things (IoT), reinforcement learning (RL) using a deep neural network, i.e., deep reinforcement learning (DRL) has been… read more here.
Keywords: use; reinforcement learning; offline monte; use based ... See more keywords