TY - JOUR AU - Hein, Anthony AU - Jiang, May AU - Thiyageswaran, Vydhourie AU - Guerzhoy, Michael PY - 2021/05/18 Y2 - 2024/03/29 TI - Random Forests for Opponent Hand Estimation in Gin Rummy JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 35 IS - 17 SE - EAAI Symposium: Full Papers DO - 10.1609/aaai.v35i17.17830 UR - https://ojs.aaai.org/index.php/AAAI/article/view/17830 SP - 15545-15550 AB - We demonstrate an AI agent for the card game of Gin Rummy. The agent uses simple heuristics in conjunction with a model that predicts the probability of each card's being in the opponent's hand. To estimate the probabilities for cards' being in the opponent's hand, we generate a dataset of Gin Rummy games using self-play, and train a random forest on the game information states. We explore the random forest classifier we trained and study the correspondence between its outputs and intuitively correct outputs. Our agent wins 61% of games against a baseline heuristic agent that does not use opponent hand estimation. ER -