1. How does reinforcement learning involve a conversation between an agent and an environment? Explain the key elements of this interaction. Include relevant timestamps in your answer.
2. How does the computation in reinforcement learning differ from the computation in a Markov Decision Process (MDP)? Explain the role of the agent and the environment in this context. Include relevant timestamps in your answer.
3. Put yourself in the shoes of an agent in a reinforcement learning environment. Describe how you would interact with the environment and how you could potentially build a model of the environment. Include relevant timestamps in your answer.
What are the main challenges of reinforcement learning,
and how to overcome them?
How to Structure, Organize, Track and Manage
Reinforcement Learning (RL) Projects
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