DocumentCode
3474865
Title
Boosting Blackjack Returns with Machine Learned Betting Criteria
Author
Coleman, Ron
Author_Institution
Dept. of Comput. Sci., Marist Coll., Poughkeepsie, NY
fYear
2006
fDate
10-12 April 2006
Firstpage
669
Lastpage
673
Abstract
This paper investigates a new method to boost Blackjack betting returns. We show betting criteria identified by genetic algorithm significantly outperform standard game theoretic criteria on ten different professional counting systems
Keywords
game theory; genetic algorithms; learning (artificial intelligence); Blackjack betting return boosting; betting game theoretic criteria; counting system; game theory; genetic algorithm; machine learning; Boosting; Cellular phones; Computer science; Consumer electronics; Educational institutions; Game theory; Genetic algorithms; Machine learning; Mobile computing; Personal digital assistants;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology: New Generations, 2006. ITNG 2006. Third International Conference on
Conference_Location
Las Vegas, NV
Print_ISBN
0-7695-2497-4
Type
conf
DOI
10.1109/ITNG.2006.40
Filename
1611681
Link To Document