Finding Blackjack's Optimal Strategy in Real-time and Player's Expected Win
Jarek Solowiej
Abstract
We describe the probability theory behind a casino game, blackjack, and the procedure to compute the optimal strategy for a deck of arbitrary cards and player's expected win given that he follows the optimal strategy. The exact blackjack probabilities are used, in contrast to approximate probabilities used by Baldwin et al. BCMM or Monte Carlo methods. We distinguish between two probability measures P and Q; P is used to compute dealer's probabilities and Q is used to compute player's expectations. The implementation is described in pseudo-C++. The program is fast enough to deal with any blackjack's hand in a matter of seconds.
Create a lesson
Related papers
Stable Movement for Nondual Lipschitz Convex Optimization: Efficiency and Nearly Optimal Oracle Rates
David Martínez-Rubio, Cristóbal Guzmán
The First-Order Oracle Complexity of Lipschitz Convex Optimization in Nondual Settings
David Martínez-Rubio, Brian Bullins, Cristóbal Guzmán et al.
Complexity Of Output Feedback Stabilization
Amir Ali Ahmadi, Abraar Chaudhry, Ijay Narang et al.
Convergence rate of the moment-SOS hierarchy for univariate polynomial optimization
Didier Henrion, Mohab Safey El Din
Geometry and Convergence of Quadratically Regularized Optimal Transport I
Alberto González-Sanz, Marcel Nutz
Constraint Qualifications and Gradient Flows for Block Vanishing Constraint Problems
Julian Niederer, Christoph Hansknecht, Andreas Potschka et al.