Probabilistic Computation

Probabilistic computation is a method in theoretical computer science that incorporates randomness into algorithms. Instead of providing a definite outcome every time, these algorithms use random choices to make decisions or solve problems. This can lead to faster solutions for complex problems, especially when exact answers are hard to compute. They are often used in areas like cryptography, optimization, and machine learning. By leveraging probability, these algorithms can achieve high accuracy or efficiency, even if they don’t always produce the same result with each execution. Essentially, it combines certainty with chance to enhance computational processes.