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.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OGU.10214/6645 |
| Date | 07 May 2013 |
| Creators | Altman, Benjamin |
| Contributors | Nonnecke, Blair |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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