A Highly-Parameterized Ensemble to Play Gin Rummy

Masayuki Nagai, Kavya Shrivastava, Kien Ta, Steven Bogaerts, Chad Byers
2021 AAAI Conference on Artificial Intelligence  
This paper describes the design and training of a computer Gin Rummy player. The system includes three main components to make decisions about drawing cards, discarding, and ending the game, with numerous parameters controlling behavior. In particular, an ensemble approach is explored in the discard decision. Finally, three sets of parameter tuning and performance experiments are analyzed. Tracking the State of a Round Let self represent the computer player and opp the opponent. In this paper, opp is always the same: the simple player that
dblp:conf/aaai/NagaiSTBB21 fatcat:3efjuji6qvcg5ofokrwegveoqy