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In a previous post we set-up the OpenAI Gym to interface with our Javascript environment. Let's now look at how we can use this interface to run the CartPole example and solve it with the theory that we learned in previous blog posts. Requirements: * An introduction to

Summary So what did we learn up until now in our Introduction and Markov Property, Chain, Reward Process and Decision Process posts? Initially we defined our basic concepts: * State: What does our current environment look like? * Action: What action are we taking? * Policy: When taking action $a$ in state $s$

As seen in the previous article, we now know the general concept of Reinforcement Learning. But how do we actually get towards solving our third challenge: "Temporal Credit Assignment"? To solve this, we first need to introduce a generalization of our reinforcement models. When we look at these