A complete deep Q-learner to solve complex problems with raw pixel input

From the beginning of this chapter, we have implemented several additional techniques and utility tools to improve the agent. In this section, we will consolidate all the improvements and the utility tools we have discussed so far into a unified deep_Q_Learner.py script. We will be using this unified agent script to train on the Atari Gym environment in the next section and watch the agent improving its performance and fetching more and more scores over time.

The following code is the unified version that utilizes the following features that we developed in the previous sections of this chapter:

  • Experience memory
  • Experience replay to learn from (mini) batches of experience ...

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