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.

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 ...

The multi-armed bandit is an algorithm family, while the Bayesian approach is the way to interpret collated data and provide experiment results using a set of formulas from Bayesian statistics.

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 ...

We propose an asymptotically optimal heuristic, which we term randomized assignment control (RAC) for a restless multi-armed bandit problem with discrete-time and finite states. It is constructed ...