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Hiding Behind Cards: Identifying Bots and Humans in Online Poker

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dc.contributor.advisor Nonnecke, Blair
dc.contributor.author Altman, Benjamin
dc.date.accessioned 2013-05-07T18:42:56Z
dc.date.available 2013-05-07T18:42:56Z
dc.date.copyright 2013-05
dc.date.created 2013-05-02
dc.date.issued 2013-05-07
dc.identifier.uri http://hdl.handle.net/10214/6645
dc.description.abstract As online gaming becomes more popular, it has also become increasingly important to identify and remove those who leverage automated player systems (bots). Manual bot detection depends on the ability of game administrators to differentiate between bots and normal players. The objective of this thesis was to determine whether expert poker players can differentiate between bot and human players in Texas Hold ‘Em Poker. Participants were deceived into thinking a number of bots and humans were playing in gameplay videos and asked to rate player botness and skill. Results showed that participants made similar observations about player behaviour, yet used these observations to reach differing conclusions about whether a given player was a bot or a human. These results cast doubt on the reliability of manual bot detection systems for online poker, yet also show that experts agree on what constitutes skilled play within such an environment. en_US
dc.language.iso en en_US
dc.subject poker en_US
dc.subject bots en_US
dc.subject bot detection en_US
dc.subject bot vs human en_US
dc.subject computer player en_US
dc.subject game bots en_US
dc.subject bot gameplay en_US
dc.title Hiding Behind Cards: Identifying Bots and Humans in Online Poker en_US
dc.type Thesis en_US
dc.degree.programme Computer Science en_US
dc.degree.name Master of Science en_US
dc.degree.department School of Computer Science en_US
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