Black-Box Optimization in RL
In this chapter, we will change our perspective on reinforcement learning (RL) training again and switch to the so-called black-box optimizations. In particular, this chapter will cover two examples of black-box optimization methods:
- Evolution strategies
- Genetic algorithms
These methods are at least a decade old, but recently, several research studies were conducted that showed the applicability of the methods to large-scale RL problems, and their competitiveness with the value iteration and policy gradient methods.