Showing cs.AIShow all
3 papers · 1 filter
cs.AI2019
Policy Based Inference in Trick-Taking Card Games
Douglas Rebstock, Christopher Solinas, Michael Buro +1
Trick-taking card games feature a large amount of private information that slowly gets revealed through a long sequence of actions. This makes the number of histories exponentially…
cs.AI2019
Learning Policies from Human Data for Skat
Douglas Rebstock, Christopher Solinas, Michael Buro
Decision-making in large imperfect information games is difficult. Thanks to recent success in Poker, Counterfactual Regret Minimization (CFR) methods have been at the forefront of…
cs.AI2019
Improving Search with Supervised Learning in Trick-Based Card Games
Christopher Solinas, Douglas Rebstock, Michael Buro
In trick-taking card games, a two-step process of state sampling and evaluation is widely used to approximate move values. While the evaluation component is vital, the accuracy of…