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  • We will first understand the cartpole environment of OpenAI gym.

  • We will then proceed to make a simple hard-coded policy, make the agent with that policy, and examine the performance.

  • Then we train a neural network and observe the performance.

  • Later, we learn a concept named credit assignment problem, understand the policy gradients algorithm, and implement it to observe its effect in the improvement of the game.

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