Chapter 4. The Cross-Entropy Method

In this chapter, we will wrap up the part one of the book and get familiar with one of the RL methods—cross-entropy. Despite the fact that it is much less famous than other tools in the RL practitioner's toolbox, such as deep Q-network (DQN) or Advantage Actor-Critic, this method has its own strengths. The most important are as follows:

  • Simplicity: The cross-entropy method is really simple, which makes it an intuitive method to follow. For example, its implementation on PyTorch is less than 100 lines of code.
  • Good convergence: In simple environments that don't require complex, multistep policies to be learned and discovered and have short episodes with frequent rewards, cross-entropy usually works very well. Of ...

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