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Deep Reinforcement Learning Hands-On by Maxim Lapan

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Chapter 2. OpenAI Gym

After talking so much about the theoretical concepts of RL, let's start doing something practical. In this chapter, we'll learn the basics of the OpenAI Gym API and write our first randomly behaving agent to make ourselves familiar with all the concepts.

The anatomy of the agent

As we saw in the previous chapter, there are several entities in RL's view of the world:

  • Agent: A person or a thing that takes an active role. In practice, it's some piece of code, which implements some policy. Basically, this policy must decide what action is needed at every time step, given our observations.
  • Environment: Some model of the world, which is external to the agent and has the responsibility of providing us with observations and giving us rewards. ...

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