Dempster-Shafer Theory
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 probabilities to events, it uses belief functions to express the degree of belief in various outcomes based on available evidence.
This theory is particularly useful in situations where information is incomplete or ambiguous. By representing uncertainty with basic probability assignments, it enables the aggregation of evidence and helps in identifying the most plausible conclusions, making it valuable in fields like artificial intelligence and decision-making.