Next, we will talk about the topic of exploration in reinforcement learning (RL). It has been mentioned several times in the book that the exploration/exploitation dilemma is a fundamental thing in RL and very important for efficient learning. However, in the previous examples, we used quite a trivial approach to exploring the environment, which was, in most cases, -greedy action selection. Now it's time to go deeper into the exploration subfield of RL.
In this chapter, we will:
- Discuss why exploration is such a fundamental topic in RL
- Explore the effectiveness of the epsilon-greedy (-greedy) approach
- Take a look at alternatives and try them on different environments