Innovative applications and challenges of dobby slot machine algorithms in online gaming

With the rapid development of the online gaming industry, how to improve user experience, optimise game design and increase business revenue through intelligent algorithms has become a key issue in the industry. The Multi-armed Gambling Machine (MAB) algorithm, as a classic reinforcement learning problem, has shown great potential for decision optimisation in online games. By balancing the strategy of ‘ exploration and development ’ , the MAB algorithm gradually optimises decision making in an uncertain environment, enhancing the personalised gaming experience, optimising the economic system and improving player retention. This paper reviews the innovative application of the MAB algorithm in online games, focuses on its application in game design, personalised recommendation, game economic system and player retention optimisation, discusses the challenges of the MAB algorithm in practical application and proposes future research directions. Through an overview of existing research results, this paper aims to provide a comprehensive perspective for academia and industry to promote the further development and application of the MAB algorithm in online games.