In this chapter, we will continue our exploration of the world of Reinforcement Learning (RL), focusing our attention on complex algorithms that can be employed to solve difficult problems. As this is still the introductory part of RL (the whole topic is extremely large), the structure of the chapter is based on many practical examples that can be used as a basis to work on more complex scenarios.

The topics that will be discussed in this chapter are:

• TD(λ) algorithm
• Action-Critic TD(0)
• SARSA
• Q-learning
• Q-learning with a simple visual input and a neural network