Understanding Black-Box Optimization Algorithms

In the previous chapters, we looked at reinforcement learning algorithms, ranging from value-based to policy-based methods and from model-free to model-based methods. In this chapter, we'll provide another solution for solving sequential tasks, that is, with a class of black-box algorithms evolutionary algorithms (EA). EAs are driven by evolutionary mechanisms and are sometimes preferred to reinforcement learning (RL) as they don't require backpropagation. They also offer other complementary benefits to RL. We'll start this chapter by giving you a brief recap of RL algorithms so that you'll better understand how EA fits into these sets of problems. Then, you'll learn about the basic building blocks of EA and how those algorithms work. We'll also take advantage of this introduction and look at one of...