Author(s): alopix
Originally published on Towards AI.
Mathematical and reinforcement learning tours through blackjack, poker, slot machines and roulette
Casinos are one of the few environments where the rules are public, the odds are fixed, and the house edge is mathematically guaranteed. This makes them terrible places to make money but excellent places to study reinforcement learning. In this article, I am going to use classic casino games as a learning environment for intelligent agents. Along the way, you’ll see:
The article explores the challenges and limitations of using reinforcement learning in a casino environment, showing how even with the best strategies, players cannot overcome the house edge due to the mathematical principles of probability. Through examples from various games such as blackjack, poker, slot machines, and roulette, the author explains how, without exception, the expected outcomes remain negative for players, emphasizing the importance of understanding these dynamics in the context of gambling and real-world decision making.
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Published via Towards AI
