Artificial intelligence applied to games is a typical application. IBM’s deep blue chess program beat Gary Kasparov in 1997 after a 15 year development period.
Blackjack is one of the few casino games where the odds of winning are not totally tilted in favour of the casino. The game is relatively simple:
1. The player plays against the dealer for Blackjack where the player and dealer holds an Ace and 10 or Face Card totalling 21 points. It can be the case that the player holds 21 in three cards. This case is not blackjack.
2. Bets are placed before each player and dealer are dealt two cards.
3. The dealer deals players cards face up.
4. The dealer deals themselves two cards – one up and one down. The game revolves around guessing that the dealer has Blackjack or the highest valued hand.
5. If the player breaks 21, they bust and lose all their bets.
6. The game has six player decision points:
a. Stand – take no further action to improve the player’s hand.
b. Hit – take another card and bet the action will result in 21.
c. Split If the player has a pair of face cards valued at 10 points each, two the hand may be split into two in the hope that the player will be dealt an ace.
d. Double Down – enables player to add a new hand to their initial hand.
e. Surrender – player exits round losing one half if the initial bet.
The iBlackjack application applies eLearning techniques to learn of the optimal next dealer and player move. The system will deploy a dealer robot which mimics the role of the dealer. Similarly one or more player bots and a human player would be implemented.
The system is under development.
The basic technology stack includes:
1. Java Standard Edition v9
2. Eclipse Oxygen 2
3. Apache Tomcat for web services, messaging, and HTML 5 interface functions.
4. Docker virtual application containers.
5. Amazon Web Services as the host environment.
6. MySQL relational database system
7. Encrypted user repository database.