Yao's Principle

Yao's Principle is a concept in computer science that helps estimate the best possible performance of algorithms solving uncertain problems. It states that the worst-case efficiency of any randomized algorithm (which uses randomness to make decisions) can be understood by analyzing the performance of the best deterministic algorithm (one that doesn't use randomness) against a carefully chosen probability distribution of inputs. Essentially, it allows researchers to find lower bounds on an algorithm’s performance by studying deterministic strategies, providing insight into the fundamental difficulty of a problem regardless of the randomization used.