Behavior Reinforcement and Machine Learning

Humans' behavior is constantly shaped by reinforcement based on what we want; for example, drinking water when thirsty or wearing a sweatshirt when cold. Machines, on the other hand, do not inherently want anything, so their behavior is driven by a utility function, such as winning in a game of chess or maintaining a strong position. For machines to learn human-like behavior, they must be designed to learn from the consequences of their actions, even though they lack intrinsic desires like humans.