Temporal Difference Models: Model-Free Deep RL for Model-Based Control
ICLR, Volume abs/1802.09081, 2018.
Model-free reinforcement learning (RL) has been proven to be a powerful, general tool for learning complex behaviors. However, its sample efficiency is often impractically large for solving challenging real-world problems, even for off-policy algorithms such as Q-learning. A limiting factor in classic model-free RL is that the learning si...More
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