The command generation model
In this part of the chapter, we will extend our baseline model with an extra submodule that will generate commands that our DQN network should evaluate. In the baseline model, commands were taken from the admissible commands list, which was taken from the extended information from the environment. But maybe we can generate commands from the observation using the same techniques that we covered in the previous chapter.
The architecture of our new model is shown in Figure 15.12.
Figure 15.12: The architecture of the DQN with command generation
In comparison with Figure 15.3 from earlier in the chapter, there are several changes here. First of all, our preprocessor pipeline no longer accepts a command sequence in the input. The second difference is that the preprocessor's output now not only gets passed to the DQN model, but it also forks to the "Commands generator" submodule.
