Summary
The software engineering community sometimes overlooks reinforcement learning algorithms. Let's hope that this chapter provides adequate answers to the following questions:
What is reinforcement learning?
What are the different types of algorithms that qualify as reinforcement learning?
How can we implement the Q-learning algorithm in Scala?
How can we apply Q-learning to the optimization of option trading?
What are the pros and cons of using reinforcement learning?
What are learning classifier systems?
What are the key components of the XCS algorithm?
What are the potentials and limitations of learning classifier systems?
This concludes the introduction of the last category of learning techniques. The ever-increasing amount of data that surrounds us requires data processing and machine learning algorithms to be highly scalable. This is the subject of the next and the final chapter.
