Brief overview of the Multi-Armed Bandit in Reinforcement Learning
Introduction Multi-arm bandits are one of the fundamental problems in reinforcement learning. The problem can be described as follows: there are multiple slot machines (arms), each with a different reward distribution, and the objective is to find the machine with the highest expected reward by playing them sequentially. This problem is…
Brief overview of the Multi-Armed Bandit in Reinforcement Learning Introduction Multi-arm bandits are one of the fundamental problems in reinforcement learning. The problem can be described as follows: there are multiple slot machines (arms), each with a different reward distribution, and the objective is to find the machine with the highest expected reward by playing them sequentially. This problem is… deep-learning
Brief overview MultiArmed Bandit Reinforcement Learning Introduction Multiarm bandit one fundamental problem reinforcement learning problem described follows multiple slot machine arm different reward distribution objective find machine highest expected reward playing sequentially problem is… deeplearning