On evolutionary selection of blackjack strategies
This work addresses strategy optimization in blackjack, but it is incremental as it applies an existing method to a well-studied domain without broad impact.
The researchers tackled the problem of optimizing blackjack basic strategies using evolutionary programming, finding that a population of random strategies evolved to profitable performance in about 100 generations, with results resembling known strategies in performance.
We apply the approach of evolutionary programming to the problem of optimization of the blackjack basic strategy. We demonstrate that the population of initially random blackjack strategies evolves and saturates to a profitable performance in about one hundred generations. The resulting strategy resembles the known blackjack basic strategies in the specifics of its prescriptions, and has a similar performance. We also study evolution of the population of strategies initialized to the Thorp's basic strategy.