Multi-Armed Bandit (MAB) algorithms have emerged as a vital tool in wireless networks, where they underpin adaptive decision-making processes essential for efficient resource management. These ...

A technical paper titled “MABFuzz: Multi-Armed Bandit Algorithms for Fuzzing Processors” was published by researchers at Texas A&M University and Technische Universitat Darmstadt. “As the complexities ...

Imagine you’re a gambler and you’re standing in front of several slot machines. Your goal is to maximize your winnings, but you don’t actually know anything about the potential rewards offered by each ...

A/B testing is popular among digital marketers, content strategists and web designers—and for good reason. Apart from increasing a website’s conversion rates, it also improves user engagement, comes ...

How does a gambler maximize winnings from a row of slot machines? This is the inspiration for the "multi-armed bandit problem," a common task in reinforcement learning in which "agents" make choices ...

This paper considers the use of a simple posterior sampling algorithm to balance between exploration and exploitation when learning to optimize actions such as in multiarmed bandit problems. The ...

Thompson Sampling is an algorithm that can be used to analyze multi-armed bandit problems. Imagine you're in a casino standing in front of three slot machines. You have 10 free plays. Each machine ...

Who would have thought there was a thing such as a 'multi-arm bandit algorithm'? Of course, it's the branch of mathematics that models how a gambler deals with an entire row of one-arm bandit machines ...