B1 Non-refereed article in a scientific journal
Detecting a Colluding Subset in a Simple Two-Dimensional Game
Authors: Jussi Laasonen, Jouni Smed
Publication year: 2013
Journal: TUCS Publication Series
Volume: 1074
ISSN: 1239-1891
Abstract
Collusion is covert co-operation between the participants of a game. Detecting the colluding players can require discerning and understanding the player's motivation, which is often difficult task even for humans. In this paper we analyse experimental data from a simple two-dimensional game using synthetic players. We calculate information gains of the features in the data to show how well they indicate collusion. Then we examine J4.8 decision tree classifiers learned from the data and use them to detect the colluding subsets.
Collusion is covert co-operation between the participants of a game. Detecting the colluding players can require discerning and understanding the player's motivation, which is often difficult task even for humans. In this paper we analyse experimental data from a simple two-dimensional game using synthetic players. We calculate information gains of the features in the data to show how well they indicate collusion. Then we examine J4.8 decision tree classifiers learned from the data and use them to detect the colluding subsets.
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