Enhancing Poker Agents with Hand History Statistics
| Type of publication: | Mastersthesis |
| Citation: | ba:Li |
| Type: | Bachelor-Arbeit |
| Year: | 2013 |
| Month: | May |
| School: | TU Darmstadt, Knowledge Engineering Group |
| URL: | /lehre/arbeiten/bachelor/2013/Li_Andreas.pdf |
| Abstract: | Poker is one of the more recent topics in the research field of artificial intelligences. The increasing popularity of online poker has led to development of new software which helps online poker players to gain an advantage over other players. The software displays dynamically calculated statistics for each player which can help to make the right decisions at the poker table and can also help the player in finding weaknesses in their own play. In this work we want to evaluate the viability of these statistics in terms of usage in poker agents with the means of mathematical statistics and machine learning. Finally we summarize our findings and propose how these statistics can be used in poker agents. |
| Userfields: | betreuer={ELM,FJ} |
| Keywords: | database, hand histories, poker |
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