With a basic understanding of reinforcement learning, you are now in a better state (hopefully you are not in a strictly Markov state where you have forgotten the history/things you have learned so far) to understand the basics of the cool new suite of algorithms that have been rocking the field of AI in recent times.
Deep reinforcement learning emerged naturally when people made advancements in the deep learning field and applied them to reinforcement learning. We learned about the state-value function, action-value function, and policy. Let's briefly look at how they can be represented mathematically or realized through computer code. The state-value function is a real-value function that takes the current state ...
