Reinforcement learning is a sub-area of machine learning and thus also a method of artificial intelligence. Reinforcement learning ensures that our AI engine continues to develop in a self-learning manner. It works in a similar way to instrumental conditioning, where, for example, a dog learns to retrieve a ball. In this case, the dog is an agent that perceives its environment. When a trainer throws a ball away, it can run after the ball and bring it back to the trainer, thus receiving a reward. Just like the dog, the AI engine must be able to perceive digital commerce and decide on an action, such as displaying a certain brand to a customer. If the customer buys the product, the AI engine receives a digital treat. This reward reinforces the AI engine’s behaviour. This means that if a similar customer is in the online shop later, it is more likely to behave in this way again. Learn more about reinforcement learning in our blog article.