Improving State Evaluation, Inference, and Search in Trick-Based Card Games
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1407-1412.
Abstract
Skat is Germany's national card game played by millions of players around the world. In this paper, we present the world's first computer skat player that plays at the level of human experts. This performance is achieved by improving state evaluations using game data produced by human players and by using these state evaluations to perform inference on the unobserved hands of opposing players. Our results demonstrate the gains from adding inference to an imperfect information game player and show that training on data from average human players can result in expert-level playing strength.Michael Buro, Jeffrey Richard Long, Timothy Furtak, Nathan Sturtevant
@inproceedings{ijcai2009p236,
title = {Improving State Evaluation, Inference, and Search in Trick-Based Card Games},
author = {Buro, Michael and Long, Jeffrey Richard and Furtak, Timothy and Sturtevant, Nathan R.},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {1407--1412},
year = {2009},
url = {https://ijcai.org/proceedings/2009/236},
}
TY - CPAPER TI - Improving State Evaluation, Inference, and Search in Trick-Based Card Games AU - Buro, Michael AU - Long, Jeffrey Richard AU - Furtak, Timothy AU - Sturtevant, Nathan R. T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 1407 EP - 1412 UR - https://ijcai.org/proceedings/2009/236 ER -Copied
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