Why is decision-making so difficult? There are three main reasons: first, our limited ability in computing optimal strategies; second, the incomplete knowledge of the world around us; third, the inaccuracy of the predictions about the consequences of our actions. Under this severe conditions, is it still possible to act optimally? With the aid of examples from biology, medicine and computer science, I will discuss how the theory of Markov Decision Processes and Reinforcement Learning provides an answer to this question.