Do More Experienced Gamblers Choose Slot Machines with Better Odds? A Large-Scale Multi-Armed Bandit Problem at a Casino

Ye Hu () and Stowe Shoemaker
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Ye Hu: University of Houston
Stowe Shoemaker: University of Nevada

Customer Needs and Solutions, 2024, vol. 11, issue 1, No 9, 18 pages

Abstract: Abstract Conventional wisdom in casino gaming research suggests that gamblers are unable to identify slot machines with better odds. However, this study challenges that notion by examining whether experienced players, with years of casino play, can make informed decisions to optimize their chances of winning. With real gambling data, our findings reveal that seasoned players tend to favor slot machines with better odds. Interestingly, they refine their choices during less crowded hours when availability constraints are eased. Furthermore, consistent with the tradeoff between exploitation and exploration in reinforcement learning, more experienced players exhibit higher consistency in slot machine selection over time, suggesting genuine knowledge of which machines offer better odds. These results have significant implications for understanding casino player behavior and the potential for human learning to optimize complex decisions in a large-scale multi-armed bandit problem.

Keywords: Casino gaming; Slot machines; Armed-bandit problem; Experience; Reinforcement learning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s40547-024-00150-5

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