This paper presents an introduction to reinforcement learning and relational reinforcement learning at a level to be understood by students and researchers with different backgrounds. It gives an overview of the fundamental principles and techniques of reinforcement learning without involving a rigorous deduction of the mathematics involved through the use of an example application. Then, relational reinforcement learning is presented as a combination of reinforcement learning with relational learning. Its advantages - such as the possibility of using structural representations, making abstraction from specific goals pursued and exploiting the results of previous learning phases - are discussed.