Automatic Bidding for the Game of Skat

Authors:
Thomas Keller;Sebastian Kupferschmid
Affiliations:
University of Freiburg, Germany;University of Freiburg, Germany
Venue:
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Year:
2008

Citing 4
Cited 0

Search in games with incomplete information: a case study using Bridge card play

Artificial Intelligence
Machine Learning

Machine Learning
GIB: steps toward an expert-level bridge-playing program

IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
A skat player based on Monte-Carlo simulation

CG'06 Proceedings of the 5th international conference on Computers and games

Quantified Score

Hi-index	0.00

Visualization

Abstract

In recent years, researchers started to study the game of Skat. The strength of existing Skat playing programs is definitely the card play phase. The bidding phase, however, has been treated quite poorly so far. This is a severe drawback since bidding abilities influence the overall playing performance drastically. In this paper we present a powerful bidding engine which is based on a k-nearest neighbor algorithm.