no code implementations • 30 Dec 2021 • Bin Chong, Yingguang Yang, Zi-Le Wang, Hang Xing, Zhirong Liu
Most algorithms for the multi-armed bandit problem in reinforcement learning aimed to maximize the expected reward, which are thus useful in searching the optimized candidate with the highest reward (function value) for diverse applications (e. g., AlphaGo).