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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Senyo Simpson discusses how Rust's core ...

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 ...