Deep Recurrent Q network, as discussed in previous article, can be very helpful in building smart agents that remember their learning from distant past. This feature makes a Deep Recurrent Q network a valuable function approximator in building AI agents for Deep Reinforcement Learning.
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This series of posts is an attempt to help those who are in this pursuit and introduce them to the world of Data using the most widely popular language – R. Here is a collection of the first 12 articles.