‘Exploration vs. Exploitation’ is a central concept of artificial intelligence. It enables learning in unknown environments where prior knowledge is not available. It basically means that an AI will first explore its environment randomly to test possible solutions for a problem. When these are found, they provide a basic knowledge to figure out the optimal solution. However, it is important to keep a certain balance between exploring and exploiting: how often should new solutions be tested? How much of the knowledge gain from the initial strategy do you use before switching to a different action or strategy?