Score-based Bayesian skill learning
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Guo, Shengbo; Sanner, Scott; Buntine, Wray; Graepel, Thore
Description
We extend the Bayesian skill rating system of TrueSkill to accommodate score-based match outcomes. TrueSkill has proven to be a very effective algorithm for matchmaking - the process of pairing competitors based on similar skill-level - in competitive online gaming. However, for the case of two teams/players, TrueSkill only learns from win, lose, or draw outcomes and cannot use additional match outcome information such as scores. To address this deficiency, we propose novel Bayesian graphical...[Show more]
Collections | ANU Research Publications |
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Date published: | 2012 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/69102 |
Source: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
DOI: | 10.1007/978-3-642-33460-3_12 |
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