Dempster-Shafer theory is a mathematical framework for reasoning with uncertainty. It allows for the combination of evidence from different sources to make decisions or draw conclusions. Instead of assigning a single probability to an event, it uses belief functions to express the degree of belief based on available evidence. This theory is particularly useful in situations where information is incomplete or ambiguous. By representing uncertainty with intervals of belief, it provides a more flexible approach than traditional probability methods. This makes it applicable in various fields, including artificial intelligence, robotics, and decision-making systems.