| dc.description.abstract | Collusion refers to secret, illegal cooperation among competitors to gain an un
fair advantage, often at the expense of others. This type of behavior is strongly
condemned and sanctioned, but remains difficult to detect, resulting in too many
players being insufficiently deterred from unfair play. In online poker, this is
an ongoing issue, because real money is at stake and the strategic deviations
stemming from collusion are often subtle and hard to recognize. This thesis
addresses this issue by introducing a formal model of collusion in Pot Limit
Omaha poker, where players can collude by secretly revealing their cards to one
another. This thesis uses Counterfactual Regret Minimization to approximate
the strategies of colluding and non-colluding players in this model, showing how
the model can be used to identify or approximate behavior associated with collusion. The strategies that were identified revealed significant advantages for
colluding players, highlighting the severity of the issue and the need for further
research into collusion detection, which may utilize the model developed in this
research as the foundation | |
