Summary

In this chapter, you saw two examples of black-box optimization methods: evolution strategies and genetic algorithms, which can provide competition for other analytical gradient methods. Their strength lies in good parallelization on a large number of resources and the smaller number of assumptions that they have on the reward function.

In the next chapter, we will take a look at a very important aspect of RL: advanced exploration methods.